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ORCIDGeorge Karypis
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- affiliation: University of Minnesota, USA
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2020 – today
- 2024
[j87]Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola:
Multimodal Chain-of-Thought Reasoning in Language Models. Trans. Mach. Learn. Res. 2024 (2024)- [j86]Zonghan Wu
, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis:
TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2003-2013 (2024) - [c236]Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis:
Extreme Miscalibration and the Illusion of Adversarial Robustness. ACL (1) 2024: 2500-2525 - [c235]Rami Aly, Zhiqiang Tang, Samson Tan, George Karypis:
Learning to Generate Answers with Citations via Factual Consistency Models. ACL (1) 2024: 11876-11896 - [c234]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
Revisit Orthogonality in Graph-Regularized MLPs. CIKM 2024: 3145-3154 - [c233]Luyi Ma, Xiaohan Li, Kamilia Ahmadi, Jianpeng Xu, Philip S. Yu, George Karypis:
3rd International Workshop on Industrial Recommendation Systems (IRS). CIKM 2024: 5588-5591 - [c232]Zeren Shui, Petros Karypis, Daniel S. Karls, Mingjian Wen, Saurav Manchanda, Ellad B. Tadmor, George Karypis:
Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification. EMNLP (Findings) 2024: 16718-16732 - [c231]Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen, Jiani Zhang, Huzefa Rangwala, Christos Faloutsos, George Karypis:
CoverICL: Selective Annotation for In-Context Learning via Active Graph Coverage. EMNLP 2024: 21268-21286 - [c230]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. ICLR 2024 - [c229]Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. ICLR 2024 - [c228]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Bias-Term Fine-tuning of Foundation Models. ICML 2024 - [c227]Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. KDD 2024: 6356-6367 - [c226]Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis:
Inference Optimization of Foundation Models on AI Accelerators. KDD 2024: 6605-6615 - [c225]Yuan Ling, Shujing Dong, Yarong Feng, Zongyi Joe Liu, George Karypis, Chandan K. Reddy:
KDD workshop on Evaluation and Trustworthiness of Generative AI Models. KDD 2024: 6729-6730 - [c224]Narges Tabari, Aniket Anand Deshmukh, Wang-Cheng Kang, Hamed Zamani, Rashmi Gangadharaiah, Julian J. McAuley, George Karypis:
First Workshop on Generative AI for Recommender Systems and Personalization. KDD 2024: 6737-6738 - [c223]Petros Karypis, Julian J. McAuley, George Karypis:
Extending Input Contexts of Language Models through Training on Segmented Sequences. NAACL-HLT (Findings) 2024: 3040-3052 - [c222]Costas Mavromatis, Petros Karypis, George Karypis:
SemPool: Simple, Robust, and Interpretable KG Pooling for Enhancing Language Models. PKDD (4) 2024: 154-166 - [c221]Vachik S. Dave, Linsey Pang, Xiquan Cui, Chen Luo, Hamed Zamani, Lingfei Wu, George Karypis:
The 3rd International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom 2024). WSDM 2024: 1208-1209 - [i100]Costas Mavromatis, Petros Karypis, George Karypis:
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models. CoRR abs/2402.02289 (2024) - [i99]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. CoRR abs/2402.14361 (2024) - [i98]Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis:
Extreme Miscalibration and the Illusion of Adversarial Robustness. CoRR abs/2402.17509 (2024) - [i97]Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis:
Pre-training Differentially Private Models with Limited Public Data. CoRR abs/2402.18752 (2024) - [i96]Christos Koutras, Jiani Zhang, Xiao Qin, Chuan Lei, Vasileios Ioannidis, Christos Faloutsos, George Karypis, Asterios Katsifodimos:
OmniMatch: Effective Self-Supervised Any-Join Discovery in Tabular Data Repositories. CoRR abs/2403.07653 (2024) - [i95]Costas Mavromatis, Petros Karypis, George Karypis:
Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization. CoRR abs/2404.11531 (2024) - [i94]Zhiqiang Tang, Haoyang Fang, Su Zhou, Taojiannan Yang, Zihan Zhong, Tony Hu, Katrin Kirchhoff, George Karypis:
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models. CoRR abs/2404.16233 (2024) - [i93]Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang, Bowen Jin, Yizhou Sun, George Karypis:
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning. CoRR abs/2404.18271 (2024) - [i92]Costas Mavromatis, George Karypis:
GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning. CoRR abs/2405.20139 (2024) - [i91]Da Zheng, Xiang Song, Qi Zhu, Jiani Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: all-in-one graph machine learning framework for industry applications. CoRR abs/2406.06022 (2024) - [i90]Shichang Zhang, Da Zheng, Jiani Zhang, Qi Zhu, Xiang Song, Soji Adeshina, Christos Faloutsos, George Karypis, Yizhou Sun:
Hierarchical Compression of Text-Rich Graphs via Large Language Models. CoRR abs/2406.11884 (2024) - [i89]Rami Aly, Zhiqiang Tang, Samson Tan, George Karypis:
Learning to Generate Answers with Citations via Factual Consistency Models. CoRR abs/2406.13124 (2024) - [i88]Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis:
Inference Optimization of Foundation Models on AI Accelerators. CoRR abs/2407.09111 (2024) - [i87]Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Sheng Zha, Thomas Brox, George Karypis:
Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. CoRR abs/2409.01483 (2024) - [i86]Zeren Shui, Petros Karypis, Daniel S. Karls, Mingjian Wen, Saurav Manchanda, Ellad B. Tadmor, George Karypis:
Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification. CoRR abs/2410.13332 (2024) - [i85]Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala:
AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. CoRR abs/2410.13825 (2024) - [i84]Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor:
Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. CoRR abs/2410.14655 (2024) - 2023
- [j85]Fan Yang, Fuzhong Xue, Yanchun Zhang, George Karypis:
Kernelized Multitask Learning Method for Personalized Signaling Adverse Drug Reactions. IEEE Trans. Knowl. Data Eng. 35(2): 1681-1694 (2023) - [c220]Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis:
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI 2023: 5230-5238 - [c219]Xuming Hu, Shen Wang, Xiao Qin, Chuan Lei, Zhengyuan Shen, Christos Faloutsos, Asterios Katsifodimos, George Karypis, Lijie Wen, Philip S. Yu:
Automatic Table Union Search with Tabular Representation Learning. ACL (Findings) 2023: 3786-3800 - [c218]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. EMNLP 2023: 13276-13290 - [c217]Costas Mavromatis, George Karypis:
Global and Nodal Mutual Information Maximization in Heterogeneous Graphs. ICASSP 2023: 1-5 - [c216]Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henghui Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, Zhiheng Huang, William Yang Wang, George Karypis, Bing Xiang, Dan Roth:
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark. ICLR 2023 - [c215]Yulun Wu, Robert A. Barton, Zichen Wang, Vassilis N. Ioannidis, Carlo De Donno, Layne C. Price, Luis F. Voloch, George Karypis:
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information. ICLR 2023 - [c214]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Optimization on Large Model at Small Cost. ICML 2023: 3192-3218 - [c213]Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran:
XTab: Cross-table Pretraining for Tabular Transformers. ICML 2023: 43181-43204 - [c212]Israt Nisa, Minjie Wang, Da Zheng, Qiang Fu, Ümit V. Çatalyürek, George Karypis:
Optimizing Irregular Dense Operators of Heterogeneous GNN Models on GPU. IPDPS Workshops 2023: 199-206 - [c211]Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy:
International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models. KDD 2023: 5868-5869 - [c210]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. NeurIPS 2023 - [c209]Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis:
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS 2023 - [c208]Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis:
Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS 2023 - [c207]Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis:
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. ECML/PKDD (3) 2023: 157-173 - [c206]Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis:
DSP: Efficient GNN Training with Multiple GPUs. PPoPP 2023: 392-404 - [c205]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC 2023: 39:1-39:12 - [c204]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c203]Vachik S. Dave, Linsey Pang, Xiquan Cui, Lingfei Wu, Hamed Zamani, George Karypis:
The 2nd Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom). WWW (Companion Volume) 2023: 850-853 - [i83]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization. CoRR abs/2302.00109 (2023) - [i82]Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola:
Multimodal Chain-of-Thought Reasoning in Language Models. CoRR abs/2302.00923 (2023) - [i81]Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henry Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, William Yang Wang, Zhiheng Huang, George Karypis, Bing Xiang, Dan Roth:
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark. CoRR abs/2302.06729 (2023) - [i80]Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis:
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. CoRR abs/2304.10668 (2023) - [i79]Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran:
XTab: Cross-table Pretraining for Tabular Transformers. CoRR abs/2305.06090 (2023) - [i78]Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis:
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR abs/2306.00381 (2023) - [i77]Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis:
Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR abs/2306.03438 (2023) - [i76]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR abs/2307.07649 (2023) - [i75]Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis:
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR abs/2307.08623 (2023) - [i74]Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Coupling public and private gradient provably helps optimization. CoRR abs/2310.01304 (2023) - [i73]Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan, Zhengyuan Shen, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. CoRR abs/2310.09656 (2023) - [i72]Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael R. Fellows, Lars Gottesbüren, Tobias Heuer, George Karypis, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances A. Rosamond, Ilya Safro, Sebastian Schlag, Christian Schulz, Roohani Sharma, Darren Strash, Blair D. Sullivan, Bora Uçar, Albert-Jan Yzelman:
Open Problems in (Hyper)Graph Decomposition. CoRR abs/2310.11812 (2023) - [i71]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. CoRR abs/2310.13196 (2023) - [i70]Petros Karypis, Julian J. McAuley, George Karypis:
Extending Input Contexts of Language Models through Training on Segmented Sequences. CoRR abs/2310.14633 (2023) - [i69]Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis:
On the accuracy and efficiency of group-wise clipping in differentially private optimization. CoRR abs/2310.19215 (2023) - [i68]Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen, Jiani Zhang, Huzefa Rangwala, Christos Faloutsos, George Karypis:
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection. CoRR abs/2310.20046 (2023) - [i67]Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis:
Zero redundancy distributed learning with differential privacy. CoRR abs/2311.11822 (2023) - [i66]George Karypis, Christian Schulz, Darren Strash, Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael R. Fellows, Lars Gottesbüren, Tobias Heuer, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances A. Rosamond, Ilya Safro, Sebastian Schlag, Roohani Sharma, Blair D. Sullivan, Bora Uçar, Albert-Jan Yzelman:
Recent Trends in Graph Decomposition (Dagstuhl Seminar 23331). Dagstuhl Reports 13(8): 1-45 (2023) - 2022
- [j84]Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs. Proc. VLDB Endow. 15(8): 1572-1580 (2022) - [j83]Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin:
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. Proc. VLDB Endow. 16(1): 37-50 (2022) - [j82]Zhuliu Li, Raphael Petegrosso, Shaden Smith, David Sterling, George Karypis, Rui Kuang:
Scalable Label Propagation for Multi-Relational Learning on the Tensor Product of Graphs. IEEE Trans. Knowl. Data Eng. 34(12): 5964-5978 (2022) - [j81]Maria Kalantzi, Agoritsa Polyzou, George Karypis:
FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning. IEEE Trans. Learn. Technol. 15(6): 757-770 (2022) - [j80]Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis:
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2378-2392 (2022) - [c202]Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip Ryan Howard, Tetiana Grinberg, Nagib Hakim, George Karypis:
TempoQR: Temporal Question Reasoning over Knowledge Graphs. AAAI 2022: 5825-5833 - [c201]Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He:
Meta-learning via Language Model In-context Tuning. ACL (1) 2022: 719-730 - [c200]Trong Nghia Hoang, Anoop Deoras, Tong Zhao, Jin Li, George Karypis:
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback. AISTATS 2022: 1062-1077 - [c199]Costas Mavromatis, George Karypis:
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs. EMNLP (Findings) 2022: 2447-2458 - [c198]Soji Adeshina, Jian Zhang, Muhyun Kim, Min Chen, Rizal Fathony, Advitiya Vashisht, Jia Chen, George Karypis:
PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks. ICKG 2022: 6-13 - [c197]Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc:
Nimble GNN Embedding with Tensor-Train Decomposition. KDD 2022: 2327-2335 - [c196]Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs. KDD 2022: 4582-4591 - [c195]Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina, Zak Jost, Christos Faloutsos, George Karypis:
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning. LoG 2022: 35 - [c194]Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis:
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT 2022: 2542-2550 - [c193]Zeren Shui, Daniel S. Karls, Mingjian Wen, Ilia A. Nikiforov, Ellad B. Tadmor, George Karypis:
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. NeurIPS 2022 - [c192]Ancy Sarah Tom, Nesreen K. Ahmed, George Karypis:
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach. ECML/PKDD (2) 2022: 86-103 - [c191]Jiacheng Li, Tong Zhao, Jin Li, Jim Chan, Christos Faloutsos, George Karypis, Soo-Min Pantel, Julian J. McAuley:
Coarse-to-Fine Sparse Sequential Recommendation. SIGIR 2022: 2082-2086 - [c190]George Karypis:
Graph Neural Network Research at AWS AI. WSDM 2022: 4 - [r6]Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis:
Trust Your Neighbors: A Comprehensive Survey of Neighborhood-Based Methods for Recommender Systems. Recommender Systems Handbook 2022: 39-89 - [i65]Ancy Sarah Tom, Nesreen K. Ahmed, George Karypis:
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach. CoRR abs/2201.09086 (2022) - [i64]Trong Nghia Hoang, Anoop Deoras, Tong Zhao, Jin Li, George Karypis:
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback. CoRR abs/2203.12598 (2022) - [i63]Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs. CoRR abs/2203.14883 (2022) - [i62]Jiacheng Li, Tong Zhao, Jin Li, Jim Chan, Christos Faloutsos, George Karypis, Soo-Min Pantel, Julian J. McAuley:
Coarse-to-Fine Sparse Sequential Recommendation. CoRR abs/2204.01839 (2022) - [i61]Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis:
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR abs/2204.11117 (2022) - [i60]Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin:
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. CoRR abs/2205.00119 (2022) - [i59]Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina, Zak Jost, Christos Faloutsos, George Karypis:
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning. CoRR abs/2206.04255 (2022) - [i58]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR abs/2206.07136 (2022) - [i57]Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc:
Nimble GNN Embedding with Tensor-Train Decomposition. CoRR abs/2206.10581 (2022) - [i56]Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis:
Efficient and effective training of language and graph neural network models. CoRR abs/2206.10781 (2022) - [i55]Yulun Wu, Layne C. Price, Zichen Wang, Vassilis N. Ioannidis, George Karypis:
Variational Causal Inference. CoRR abs/2209.05935 (2022) - [i54]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR abs/2210.00036 (2022) - [i53]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Optimization on Large Model at Small Cost. CoRR abs/2210.00038 (2022) - [i52]Yulun Wu, Robert A. Barton, Zichen Wang, Vassilis N. Ioannidis, Carlo De Donno, Layne C. Price, Luis F. Voloch, George Karypis:
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information. CoRR abs/2210.00116 (2022) - [i51]Zeren Shui, Daniel S. Karls, Mingjian Wen, Ilia A. Nikiforov, Ellad B. Tadmor, George Karypis:
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. CoRR abs/2210.08047 (2022) - [i50]Costas Mavromatis, George Karypis:
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs. CoRR abs/2210.13650 (2022) - [i49]Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr:
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR abs/2212.05191 (2022) - 2021
- [c189]Saurav Manchanda, George Karypis:
Importance Assessment in Scholarly Networks. SDU@AAAI 2021 - [c188]Saurav Manchanda, Da Zheng, George Karypis:
Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs. IEEE BigData 2021: 480-489 - [c187]Saurav Manchanda, Mohit Sharma, George Karypis:
Distant-Supervised Slot-Filling for E-Commerce Queries. IEEE BigData 2021: 677-686 - [c186]Maria Kalantzi, George Karypis:
Position-based Hash Embeddings For Scaling Graph Neural Networks. IEEE BigData 2021: 779-789 - [c185]Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis:
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP 2021: 119-133 - [c184]Saurav Manchanda, George Karypis:
Evaluating Scholarly Impact: Towards Content-Aware Bibliometrics. EMNLP (1) 2021: 6041-6053 - [c183]Jialin Dong, Da Zheng, Lin F. Yang, George Karypis:
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs. KDD 2021: 289-299 - [c182]Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu:
2nd International Workshop on Industrial Recommendation Systems (IRS). KDD 2021: 4173-4174 - [c181]Linfeng Liu, Hoan Nguyen, George Karypis, Srinivasan Sengamedu:
Universal Representation for Code. PAKDD (3) 2021: 16-28 - [c180]Costas Mavromatis, George Karypis:
Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs. PAKDD (1) 2021: 541-553 - [c179]Shalini Pandey, George Karypis, Jaideep Srivastava:
IACN: Influence-Aware and Attention-Based Co-evolutionary Network for Recommendation. PAKDD (2) 2021: 561-574 - [c178]Yikun Xian, Tong Zhao, Jin Li, Jim Chan, Andrey Kan, Jun Ma, Xin Luna Dong, Christos Faloutsos, George Karypis, S. Muthukrishnan, Yongfeng Zhang:
EX3: Explainable Attribute-aware Item-set Recommendations. RecSys 2021: 484-494 - [c177]Balasubramaniam Srinivasan, Da Zheng, George Karypis:
Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks. SDM 2021: 756-764 - [c176]Da Zheng, Minjie Wang, Quan Gan, Xiang Song, Zheng Zhang, George Karypis:
Scalable Graph Neural Networks with Deep Graph Library. WSDM 2021: 1141-1142 - [i48]Shalini Pandey, Andrew S. Lan, George Karypis, Jaideep Srivastava:
Learning Student Interest Trajectory for MOOCThread Recommendation. CoRR abs/2101.05625 (2021) - [i47]Shalini Pandey, George Karypis, Jaideep Srivastava:
An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset. CoRR abs/2101.06373 (2021) - [i46]Balasubramaniam Srinivasan, Da Zheng, George Karypis:
Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks. CoRR abs/2101.07773 (2021) - [i45]Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis:
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning. CoRR abs/2103.00113 (2021) - [i44]Shalini Pandey, George Karypis, Jaideep Srivastava:
IACN: Influence-aware and Attention-based Co-evolutionary Network for Recommendation. CoRR abs/2103.02866 (2021) - [i43]Linfeng Liu, Hoan Nguyen, George Karypis, Srinivasan Sengamedu:
Universal Representation for Code. CoRR abs/2103.03116 (2021) - [i42]Saurav Manchanda, Da Zheng, George Karypis:
Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs. CoRR abs/2105.00644 (2021) - [i41]Jialin Dong, Da Zheng, Lin F. Yang, George Karypis:
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs. CoRR abs/2106.06150 (2021) - [i40]Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, George Karypis:
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science. CoRR abs/2106.14232 (2021) - [i39]Maria Kalantzi, George Karypis:
Position-based Hash Embeddings For Scaling Graph Neural Networks. CoRR abs/2109.00101 (2021) - [i38]Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis:
TraverseNet: Unifying Space and Time in Message Passing. CoRR abs/2109.02474 (2021) - [i37]Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis:
Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems. CoRR abs/2109.04584 (2021) - [i36]Agoritsa Polyzou, Maria Kalantzi, George Karypis:
FaiREO: User Group Fairness for Equality of Opportunity in Course Recommendation. CoRR abs/2109.05931 (2021) - [i35]Costas Mavromatis, George Karypis:
HeMI: Multi-view Embedding in Heterogeneous Graphs. CoRR abs/2109.07008 (2021) - [i34]Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis:
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR abs/2109.11105 (2021) - [i33]Cole Hawkins, Vassilis N. Ioannidis, Soji Adeshina, George Karypis:
Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation. CoRR abs/2110.06290 (2021) - [i32]Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He:
Meta-learning via Language Model In-context Tuning. CoRR abs/2110.07814 (2021) - [i31]Fabio Broccatelli, Richard Trager, Michael Reutlinger, George Karypis, Mufei Li:
Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces. CoRR abs/2111.13964 (2021) - [i30]Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Soji Adeshina, Phillip Ryan Howard, Tetiana Grinberg, Nagib Hakim, George Karypis:
TempoQR: Temporal Question Reasoning over Knowledge Graphs. CoRR abs/2112.05785 (2021) - [i29]Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs. CoRR abs/2112.15345 (2021) - 2020
- [j79]Athanasios N. Nikolakopoulos, George Karypis:
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks. ACM Trans. Knowl. Discov. Data 14(6): 64:1-64:26 (2020) - [c175]Saurav Manchanda, George Karypis:
CAWA: An Attention-Network for Credit Attribution. AAAI 2020: 8472-8479 - [c174]Shalini Pandey, Andrew S. Lan, George Karypis, Jaideep Srivastava:
Learning Student Interest Trajectory for MOOC Thread Recommendation. ICDM (Workshops) 2020: 400-407 - [c173]Zeren Shui, George Karypis:
Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties. ICDM 2020: 492-500 - [c172]George Karypis:
GrAPL 2020 Keynote Speaker Deep Graph Library: Overview, Updates, and Future Developments. IPDPS Workshops 2020: 201 - [c171]Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis:
Scalable Graph Neural Networks with Deep Graph Library. KDD 2020: 3521-3522 - [c170]Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis:
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. IA3@SC 2020: 36-44 - [c169]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. SIGIR 2020: 739-748 - [c168]Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis:
Learning Graph Neural Networks with Deep Graph Library. WWW (Companion Volume) 2020: 305-306 - [i28]Sara Morsy, George Karypis:
Context-aware Non-linear and Neural Attentive Knowledge-based Models for Grade Prediction. CoRR abs/2003.05063 (2020) - [i27]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. CoRR abs/2004.08532 (2020) - [i26]Xiangxiang Zeng, Xiang Song, Tengfei Ma, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang, George Karypis, Feixiong Cheng:
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning. CoRR abs/2005.10831 (2020) - [i25]Vassilis N. Ioannidis, Da Zheng, George Karypis:
Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing. CoRR abs/2007.10261 (2020) - [i24]Vassilis N. Ioannidis, Da Zheng, George Karypis:
PanRep: Universal node embeddings for heterogeneous graphs. CoRR abs/2007.10445 (2020) - [i23]Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo, Xiang Song, George Price, Ninad Kulkarni, Ryan Brand, Parminder Bhatia, George Karypis:
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature. CoRR abs/2007.12731 (2020) - [i22]Costas Mavromatis, George Karypis:
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning. CoRR abs/2009.06946 (2020) - [i21]Zeren Shui, George Karypis:
Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties. CoRR abs/2009.12710 (2020) - [i20]Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis:
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR abs/2010.05337 (2020) - [i19]Maria Kalantzi, Agoritsa Polyzou, George Karypis:
FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning. CoRR abs/2011.11611 (2020) - [i18]Saurav Manchanda, Mohit Sharma, George Karypis:
Distant-Supervised Slot-Filling for E-Commerce Queries. CoRR abs/2012.08134 (2020)
2010 – 2019
- 2019
- [j78]David C. Anastasiu, George Karypis:
Parallel cosine nearest neighbor graph construction. J. Parallel Distributed Comput. 129: 61-82 (2019) - [j77]Mohit Sharma, F. Maxwell Harper, George Karypis:
Learning from Sets of Items in Recommender Systems. ACM Trans. Interact. Intell. Syst. 9(4): 19:1-19:26 (2019) - [j76]Agoritsa Polyzou, George Karypis:
Feature Extraction for Next-Term Prediction of Poor Student Performance. IEEE Trans. Learn. Technol. 12(2): 237-248 (2019) - [c167]Saurav Manchanda, Mohit Sharma, George Karypis:
Intent Term Weighting in E-commerce Queries. CIKM 2019: 2345-2348 - [c166]Sara Morsy, George Karypis:
Neural Attentive Knowledge-based Model for Grade Prediction. EDM 2019 - [c165]Shalini Pandey, George Karypis:
A Self Attentive model for Knowledge Tracing. EDM 2019 - [c164]Agoritsa Polyzou, Athanasios N. Nikolakopoulos, George Karypis:
Scholars Walk: A Markov Chain Framework for Course Recommendation. EDM 2019 - [c163]Shalini Pandey, George Karypis:
Structured Dictionary Learning for Energy Disaggregation. e-Energy 2019: 24-34 - [c162]Venkata Rohit Jakkula, George Karypis:
Streaming and Batch Algorithms for Truss Decomposition. GC 2019: 51-59 - [c161]Ancy Sarah Tom, George Karypis:
A 2D Parallel Triangle Counting Algorithm for Distributed-Memory Architectures. ICPP 2019: 45:1-45:10 - [c160]Sara Morsy, George Karypis:
A Study on Curriculum Planning and Its Relationship with Graduation GPA and Time To Degree. LAK 2019: 26-35 - [c159]Asmaa Elbadrawy, George Karypis:
UPM: Discovering Course Enrollment Sequences Associated with Success. LAK 2019: 373-382 - [c158]Prableen Kaur, Agoritsa Polyzou, George Karypis:
Causal Inference in Higher Education: Building Better Curriculums. L@S 2019: 49:1-49:4 - [c157]Athanasios N. Nikolakopoulos, Dimitris Berberidis, George Karypis, Georgios B. Giannakis:
Personalized diffusions for top-n recommendation. RecSys 2019: 260-268 - [c156]Athanasios N. Nikolakopoulos, George Karypis:
RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation. WSDM 2019: 150-158 - [c155]Mohit Sharma, George Karypis:
Adaptive matrix completion for the users and the items in tail. WWW 2019: 3223-3229 - [e11]Lisa Singh, Richard D. De Veaux, George Karypis, Francesco Bonchi, Jennifer Hill:
2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, DC, USA, October 5-8, 2019. IEEE 2019, ISBN 978-1-7281-4493-1 [contents] - [e10]Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. ACM 2019, ISBN 978-1-4503-6201-6 [contents] - [i17]Saurav Manchanda, George Karypis:
Distributed representation of multi-sense words: A loss-driven approach. CoRR abs/1904.06725 (2019) - [i16]Saurav Manchanda, George Karypis:
Text segmentation on multilabel documents: A distant-supervised approach. CoRR abs/1904.06730 (2019) - [i15]Sara Morsy, George Karypis:
Will this Course Increase or Decrease Your GPA? Towards Grade-aware Course Recommendation. CoRR abs/1904.11798 (2019) - [i14]Mohit Sharma, Jiayu Zhou, Junling Hu, George Karypis:
Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation. CoRR abs/1904.11799 (2019) - [i13]Mohit Sharma, George Karypis:
Adaptive Matrix Completion for the Users and the Items in Tail. CoRR abs/1904.11800 (2019) - [i12]Sara Morsy, George Karypis:
Sparse Neural Attentive Knowledge-based Models for Grade Prediction. CoRR abs/1904.11858 (2019) - [i11]Mohit Sharma, F. Maxwell Harper, George Karypis:
Learning from Sets of Items in Recommender Systems. CoRR abs/1904.12643 (2019) - [i10]Agoritsa Polyzou, George Karypis:
Grade prediction with course and student specific models. CoRR abs/1906.00792 (2019) - [i9]Shalini Pandey, George Karypis:
Structured Dictionary Learning for Energy Disaggregation. CoRR abs/1907.06581 (2019) - [i8]Shalini Pandey, George Karypis:
A Self-Attentive model for Knowledge Tracing. CoRR abs/1907.06837 (2019) - [i7]Ancy Sarah Tom, George Karypis:
A 2D Parallel Triangle Counting Algorithm for Distributed-Memory Architectures. CoRR abs/1907.09575 (2019) - [i6]Saurav Manchanda, Mohit Sharma, George Karypis:
Intent term selection and refinement in e-commerce queries. CoRR abs/1908.08564 (2019) - [i5]Venkata Rohit Jakkula, George Karypis:
Streaming and Batch Algorithms for Truss Decomposition. CoRR abs/1908.10550 (2019) - [i4]Athanasios N. Nikolakopoulos, George Karypis:
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks. CoRR abs/1909.03579 (2019) - [i3]Saurav Manchanda, George Karypis:
CAWA: An Attention-Network for Credit Attribution. CoRR abs/1911.11358 (2019) - 2018
- [j75]Jeremy Iverson, George Karypis:
A virtual memory manager optimized for node-level cooperative multi-tasking in memory constrained systems. Int. J. High Perform. Comput. Appl. 32(5): 744-759 (2018) - [j74]Shaden Smith, Jongsoo Park, George Karypis:
HPC formulations of optimization algorithms for tensor completion. Parallel Comput. 74: 99-117 (2018) - [j73]Lisa Singh, Amol Deshpande, Wenchao Zhou, Arindam Banerjee, Alex J. Bowers, Sorelle A. Friedler, H. V. Jagadish, George Karypis, Zoran Obradovic, Anil Vullikanti, Wangda Zuo:
NSF BIGDATA PI Meeting - Domain-Specific Research Directions and Data Sets. SIGMOD Rec. 47(3): 32-35 (2018) - [c154]Agoritsa Polyzou, George Karypis:
Feature extraction for classifying students based on their academic performance. EDM 2018 - [c153]Saurav Manchanda, George Karypis:
Text Segmentation on Multilabel Documents: A Distant-Supervised Approach. ICDM 2018: 1170-1175 - [c152]Evangelia Christakopoulou, George Karypis:
Local Latent Space Models for Top-N Recommendation. KDD 2018: 1235-1243 - [c151]Saurav Manchanda, George Karypis:
Distributed Representation of Multi-sense Words: A Loss Driven Approach. PAKDD (2) 2018: 337-349 - [c150]Shaden Smith, Kejun Huang, Nicholas D. Sidiropoulos, George Karypis:
Streaming Tensor Factorization for Infinite Data Sources. SDM 2018: 81-89 - [c149]George Karypis:
Recent Advances in Recommender Systems: Sets, Local Models, Coverage, and Errors. WWW (Companion Volume) 2018: 1369 - [p9]Evangelia Christakopoulou, Shaden Smith, Mohit Sharma, Alex Richards, David C. Anastasiu, George Karypis:
Scalability and Distribution of Collaborative Recommenders. Collaborative Recommendations 2018: 369-404 - [r5]Ying Zhao, George Karypis:
Document Clustering. Encyclopedia of Database Systems (2nd ed.) 2018 - [i2]Zhuliu Li, Raphael Petegrosso, Shaden Smith, David Sterling, George Karypis, Rui Kuang:
Scalable Label Propagation for Multi-relational Learning on Tensor Product Graph. CoRR abs/1802.07379 (2018) - 2017
- [j72]David C. Anastasiu, George Karypis:
Efficient identification of Tanimoto nearest neighbors. Int. J. Data Sci. Anal. 4(3): 153-172 (2017) - [j71]Faisal M. Almutairi, Nicholas D. Sidiropoulos, George Karypis:
Context-Aware Recommendation-Based Learning Analytics Using Tensor and Coupled Matrix Factorization. IEEE J. Sel. Top. Signal Process. 11(5): 729-741 (2017) - [c148]Qian Hu, Agoritsa Polyzou, George Karypis, Huzefa Rangwala:
Enriching Course-Specific Regression Models with Content Features for Grade Prediction. DSAA 2017: 504-513 - [c147]Shaden Smith, George Karypis:
Accelerating the Tucker Decomposition with Compressed Sparse Tensors. Euro-Par 2017: 653-668 - [c146]Shaden Smith, Xing Liu, Nesreen K. Ahmed, Ancy Sarah Tom, Fabrizio Petrini, George Karypis:
Truss decomposition on shared-memory parallel systems. HPEC 2017: 1-6 - [c145]Ancy Sarah Tom, Narayanan Sundaram, Nesreen K. Ahmed, Shaden Smith, Stijn Eyerman, Midhunchandra Kodiyath, Ibrahim Hur, Fabrizio Petrini, George Karypis:
Exploring optimizations on shared-memory platforms for parallel triangle counting algorithms. HPEC 2017: 1-7 - [c144]Shaden Smith, Alec Beri, George Karypis:
Constrained Tensor Factorization with Accelerated AO-ADMM. ICPP 2017: 111-120 - [c143]Shaden Smith, Jongsoo Park, George Karypis:
Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory. IPDPS 2017: 1058-1067 - [c142]George Karypis:
Improving Higher Education: Learning Analytics & Recommender Systems Research. RecSys 2017: 2 - [c141]Sara Morsy, George Karypis:
Cumulative Knowledge-based Regression Models for Next-term Grade Prediction. SDM 2017: 552-560 - [e9]George Karypis, Jia Zhang:
2017 IEEE International Congress on Big Data, BigData Congress 2017, Honolulu, HI, USA, June 25-30, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-1996-4 [contents] - [e8]Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele, Xindong Wu:
2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3835-4 [contents] - [e7]Raju Gottumukkala, Xia Ning, Guozhu Dong, Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele, Xindong Wu:
2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3800-2 [contents] - 2016
- [j70]Asmaa Elbadrawy, Agoritsa Polyzou, Zhiyun Ren, Mackenzie Sweeney, George Karypis, Huzefa Rangwala:
Predicting Student Performance Using Personalized Analytics. Computer 49(4): 61-69 (2016) - [j69]Agoritsa Polyzou, George Karypis:
Grade prediction with models specific to students and courses. Int. J. Data Sci. Anal. 2(3-4): 159-171 (2016) - [j68]Sara Morsy, George Karypis:
Accounting for Language Changes Over Time in Document Similarity Search. ACM Trans. Inf. Syst. 35(1): 1:1-1:26 (2016) - [c140]David C. Anastasiu, George Karypis:
Efficient Identification of Tanimoto Nearest Neighbors. DSAA 2016: 156-165 - [c139]Dominique LaSalle, George Karypis:
A Parallel Hill-Climbing Refinement Algorithm for Graph Partitioning. ICPP 2016: 236-241 - [c138]Shaden Smith, George Karypis:
A Medium-Grained Algorithm for Sparse Tensor Factorization. IPDPS 2016: 902-911 - [c137]Agoritsa Polyzou, George Karypis:
Grade Prediction with Course and Student Specific Models. PAKDD (1) 2016: 89-101 - [c136]Evangelia Christakopoulou, George Karypis:
Local Item-Item Models For Top-N Recommendation. RecSys 2016: 67-74 - [c135]Asmaa Elbadrawy, George Karypis:
Domain-Aware Grade Prediction and Top-n Course Recommendation. RecSys 2016: 183-190 - [c134]David C. Anastasiu, George Karypis:
Fast Parallel Cosine K-Nearest Neighbor Graph Construction. IA3@SC 2016: 50-53 - [c133]Shaden Smith, Jongsoo Park, George Karypis:
An exploration of optimization algorithms for high performance tensor completion. SC 2016: 359-371 - [e6]James Joshi, George Karypis, Ling Liu, Xiaohua Hu, Ronay Ak, Yinglong Xia, Weijia Xu, Aki-Hiro Sato, Sudarsan Rachuri, Lyle H. Ungar, Philip S. Yu, Rama Govindaraju, Toyotaro Suzumura:
2016 IEEE International Conference on Big Data (IEEE BigData 2016), Washington DC, USA, December 5-8, 2016. IEEE Computer Society 2016, ISBN 978-1-4673-9005-7 [contents] - 2015
- [j67]Dominique LaSalle, George Karypis:
Multi-threaded modularity based graph clustering using the multilevel paradigm. J. Parallel Distributed Comput. 76: 66-80 (2015) - [j66]Jeremy Iverson, Chandrika Kamath, George Karypis:
Evaluation of connected-component labeling algorithms for distributed-memory systems. Parallel Comput. 44: 53-68 (2015) - [j65]Asmaa Elbadrawy, George Karypis:
User-Specific Feature-Based Similarity Models for Top-n Recommendation of New Items. ACM Trans. Intell. Syst. Technol. 6(3): 33:1-33:20 (2015) - [j64]Rezwan Ahmed, George Karypis:
Algorithms for Mining the Coevolving Relational Motifs in Dynamic Networks. ACM Trans. Knowl. Discov. Data 10(1): 4:1-4:31 (2015) - [c132]David C. Anastasiu, George Karypis:
L2Knng: Fast Exact K-Nearest Neighbor Graph Construction with L2-Norm Pruning. CIKM 2015: 791-800 - [c131]Dominique LaSalle, George Karypis:
Efficient Nested Dissection for Multicore Architectures. Euro-Par 2015: 467-478 - [c130]David C. Anastasiu, Al Mamunur Rashid, Andrea Tagarelli, George Karypis:
Understanding computer usage evolution. ICDE 2015: 1549-1560 - [c129]Shaden Smith, Niranjay Ravindran, Nicholas D. Sidiropoulos, George Karypis:
SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication. IPDPS 2015: 61-70 - [c128]Asmaa Elbadrawy, R. Scott Studham, George Karypis:
Collaborative multi-regression models for predicting students' performance in course activities. LAK 2015: 103-107 - [c127]Xia Ning, George Karypis:
Recent Advances in Recommender Systems and Future Directions. PReMI 2015: 3-9 - [c126]Jeremy Iverson, George Karypis:
A Memory Management System Optimized for BDMPI's Memory and Execution Model. EuroMPI 2015: 2:1-2:10 - [c125]Shaden Smith, George Karypis:
Tensor-matrix products with a compressed sparse tensor. IA3@SC 2015: 5:1-5:7 - [c124]David C. Anastasiu, George Karypis:
PL2AP: fast parallel cosine similarity search. IA3@SC 2015: 8:1-8:8 - [c123]Dominique LaSalle, Md. Mostofa Ali Patwary, Nadathur Satish, Narayanan Sundaram, Pradeep Dubey, George Karypis:
Improving graph partitioning for modern graphs and architectures. IA3@SC 2015: 14:1-14:4 - [c122]Mohit Sharma, Jiayu Zhou, Junling Hu, George Karypis:
Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation. SDM 2015: 190-198 - [r4]Xia Ning, Christian Desrosiers, George Karypis:
A Comprehensive Survey of Neighborhood-Based Recommendation Methods. Recommender Systems Handbook 2015: 37-76 - 2014
- [j63]Dominique LaSalle, George Karypis:
MPI for Big Data: New tricks for an old dog. Parallel Comput. 40(10): 754-767 (2014) - [c121]Niranjay Ravindran, Nicholas D. Sidiropoulos, Shaden Smith, George Karypis:
Memory-efficient parallel computation of tensor and matrix products for big tensor decomposition. ACSSC 2014: 581-585 - [c120]Fan Yang, Xiaohui Yu, George Karypis:
Signaling adverse drug reactions with novel feature-based similarity model. BIBM 2014: 593-596 - [c119]William Myott, Thao Nguyen, Abhishek Chandra, George Karypis, Jon B. Weissman:
Opportunities for data-driven cloud-based mobile optimization. CTS 2014: 483-487 - [c118]Philip S. Yu, Masaru Kitsuregawa, Hiroshi Motoda, Bart Goethals, Minyi Guo, Longbing Cao, George Karypis, Irwin King, Wei Wang:
Welcome from DSAA 2014 chairs. DSAA 2014: 9-10 - [c117]David C. Anastasiu, George Karypis:
L2AP: Fast cosine similarity search with prefix L-2 norm bounds. ICDE 2014: 784-795 - [c116]Santosh Kabbur, George Karypis:
NLMF: NonLinear Matrix Factorization Methods for Top-N Recommender Systems. ICDM Workshops 2014: 167-174 - [c115]Evangelia Christakopoulou, George Karypis:
HOSLIM: Higher-Order Sparse LInear Method for Top-N Recommender Systems. PAKDD (2) 2014: 38-49 - [p8]David C. Anastasiu, Jeremy Iverson, Shaden Smith, George Karypis:
Big Data Frequent Pattern Mining. Frequent Pattern Mining 2014: 225-259 - 2013
- [j62]Andrea Tagarelli, George Karypis:
A segment-based approach to clustering multi-topic documents. Knowl. Inf. Syst. 34(3): 563-595 (2013) - [j61]Kevin W. DeRonne, George Karypis:
Pareto Optimal Pairwise Sequence Alignment. IEEE ACM Trans. Comput. Biol. Bioinform. 10(2): 481-493 (2013) - [j60]David C. Anastasiu, Byron J. Gao, Xing Jiang, George Karypis:
A novel two-box search paradigm for query disambiguation. World Wide Web 16(1): 1-29 (2013) - [c114]Roberto Interdonato, Salvatore Romeo, Andrea Tagarelli, George Karypis:
A Versatile Graph-Based Approach to Package Recommendation. ICTAI 2013: 857-864 - [c113]Dominique Lasalle, George Karypis:
Multi-threaded Graph Partitioning. IPDPS 2013: 225-236 - [c112]Santosh Kabbur, Xia Ning, George Karypis:
FISM: factored item similarity models for top-N recommender systems. KDD 2013: 659-667 - [c111]Zhonghua Jiang, George Karypis:
AREM: A Novel Associative Regression Model Based on EM Algorithm. PAKDD (1) 2013: 459-470 - [c110]Dominique LaSalle, George Karypis:
BDMPI: conquering BigData with small clusters using MPI. DISCS@SC 2013: 19-24 - [p7]David C. Anastasiu, Andrea Tagarelli, George Karypis:
Document Clustering: The Next Frontier. Data Clustering: Algorithms and Applications 2013: 305-338 - [e5]Hui Xiong, George Karypis, Bhavani Thuraisingham, Diane J. Cook, Xindong Wu:
2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5108-1 [contents] - [e4]Wei Ding, Takashi Washio, Hui Xiong, George Karypis, Bhavani Thuraisingham, Diane J. Cook, Xindong Wu:
13th IEEE International Conference on Data Mining Workshops, ICDM Workshops, TX, USA, December 7-10, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5109-8 [contents] - [e3]Gaurav Pandey, Huzefa Rangwala, George Karypis, Jake Yue Chen, Mohammed Javeed Zaki:
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics, BioKDD 2013, Chicago, IL, USA, August 11, 2013. ACM 2013, ISBN 978-1-4503-2327-7 [contents] - [e2]Qiang Yang, Irwin King, Qing Li, Pearl Pu, George Karypis:
Seventh ACM Conference on Recommender Systems, RecSys '13, Hong Kong, China, October 12-16, 2013. ACM 2013, ISBN 978-1-4503-2409-0 [contents] - 2012
- [j59]Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, Zhongzhi Shi:
Multi-view learning via probabilistic latent semantic analysis. Inf. Sci. 199: 20-30 (2012) - [j58]Xia Ning, Michael A. Walters, George Karypis:
Improved Machine Learning Models for Predicting Selective Compounds. J. Chem. Inf. Model. 52(1): 38-50 (2012) - [j57]Xia Ning, Michael A. Walters, George Karypis:
Improved Machine Learning Models for Predicting Selective Compounds. J. Chem. Inf. Model. 52(5): 1411 (2012) - [j56]Rezwan Ahmed, George Karypis:
Algorithms for mining the evolution of conserved relational states in dynamic networks. Knowl. Inf. Syst. 33(3): 603-630 (2012) - [j55]Christopher Kauffman, George Karypis:
Computational tools for protein-DNA interactions. WIREs Data Mining Knowl. Discov. 2(1): 14-28 (2012) - [c109]Jeremy Iverson, Chandrika Kamath, George Karypis:
Fast and Effective Lossy Compression Algorithms for Scientific Datasets. Euro-Par 2012: 843-856 - [c108]Xia Ning, George Karypis:
Sparse linear methods with side information for top-n recommendations. RecSys 2012: 155-162 - [c107]Giovanni Ponti, Andrea Tagarelli, George Karypis:
Topic Modeling for Segment-based Documents. SEBD 2012: 205-212 - [c106]Xia Ning, George Karypis:
Sparse linear methods with side information for Top-N recommendations. WWW (Companion Volume) 2012: 581-582 - [e1]Shuigeng Zhou, Songmao Zhang, George Karypis:
Advanced Data Mining and Applications, 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings. Lecture Notes in Computer Science 7713, Springer 2012, ISBN 978-3-642-35526-4 [contents] - 2011
- [c105]Xia Ning, Michael A. Walters, George Karypis:
Improved machine learning models for predicting selective compounds. BCB 2011: 106-115 - [c104]Zhonghua Jiang, George Karypis:
Automatic detection of vaccine adverse reactions by incorporating historical medical conditions. BCB 2011: 547-549 - [c103]Giovanni Ponti, Andrea Tagarelli, George Karypis:
A Statistical Model for Topically Segmented Documents. Discovery Science 2011: 247-261 - [c102]Rezwan Ahmed, George Karypis:
Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks. ICDM 2011: 1-10 - [c101]Xia Ning, George Karypis:
SLIM: Sparse Linear Methods for Top-N Recommender Systems. ICDM 2011: 497-506 - [p6]Christian Desrosiers, George Karypis:
A Comprehensive Survey of Neighborhood-based Recommendation Methods. Recommender Systems Handbook 2011: 107-144 - [r3]George Karypis:
METIS and ParMETIS. Encyclopedia of Parallel Computing 2011: 1117-1124 - 2010
- [j54]Rezwan Ahmed, Huzefa Rangwala, George Karypis:
Toptmh: Topology Predictor for transmembrane alpha-helices. J. Bioinform. Comput. Biol. 8(1): 39-57 (2010) - [j53]Yevgeniy Podolyan, Michael A. Walters, George Karypis:
Assessing Synthetic Accessibility of Chemical Compounds Using Machine Learning Methods. J. Chem. Inf. Model. 50(6): 979-991 (2010) - [c100]Santosh Kabbur, Eui-Hong Han, George Karypis:
Content-Based Methods for Predicting Web-Site Demographic Attributes. ICDM 2010: 863-868 - [c99]George Karypis, Srinivas Aluru, David A. Bader:
Message from the workshop chairs. IPDPS Workshops 2010: 1-2 - [c98]Christian Desrosiers, George Karypis:
Enhancing link-based similarity through the use of non-numerical labels and prior information. MLG@KDD 2010: 26-33 - [c97]Christian Desrosiers, George Karypis:
A Novel Approach to Compute Similarities and Its Application to Item Recommendation. PRICAI 2010: 39-51 - [c96]Xia Ning, George Karypis:
Multi-task Learning for Recommender System. ACML 2010: 269-284 - [p5]Nikil Wale, Xia Ning, George Karypis:
Trends in Chemical Graph Data Mining. Managing and Mining Graph Data 2010: 581-606 - [r2]Ying Zhao, George Karypis:
Document Clustering. Encyclopedia of Machine Learning 2010: 293-298
2000 – 2009
- 2009
- [j52]Christopher Kauffman, George Karypis:
LIBRUS: combined machine learning and homology information for sequence-based ligand-binding residue prediction. Bioinform. 25(23): 3099-3107 (2009) - [j51]Huzefa Rangwala, Christopher Kauffman, George Karypis:
svmPRAT: SVM-based Protein Residue Annotation Toolkit. BMC Bioinform. 10: 439 (2009) - [j50]Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal:
CONTOUR: an efficient algorithm for discovering discriminating subsequences. Data Min. Knowl. Discov. 18(1): 1-29 (2009) - [j49]Yevgeniy Podolyan, George Karypis:
Common Pharmacophore Identification Using Frequent Clique Detection Algorithm. J. Chem. Inf. Model. 49(1): 13-21 (2009) - [j48]Nikil Wale, George Karypis:
Target Fishing for Chemical Compounds Using Target-Ligand Activity Data and Ranking Based Methods. J. Chem. Inf. Model. 49(10): 2190-2201 (2009) - [j47]Xia Ning, Huzefa Rangwala, George Karypis:
Multi-Assay-Based Structure-Activity Relationship Models: Improving Structure-Activity Relationship Models by Incorporating Activity Information from Related Targets. J. Chem. Inf. Model. 49(11): 2444-2456 (2009) - [c95]Huzefa Rangwala, Christopher Kauffman, George Karypis:
A Kernel Framework for Protein Residue Annotation. PAKDD 2009: 439-451 - [c94]Christian Desrosiers, George Karypis:
Within-Network Classification Using Local Structure Similarity. ECML/PKDD (1) 2009: 260-275 - [c93]Xia Ning, George Karypis:
The Set Classification Problem and Solution Methods. SDM 2009: 847-858 - [p4]Chandrika Kamath, Nikil Wale, George Karypis, Gaurav Pandey, Vipin Kumar, Krishna Rajan, Nagiza F. Samatova, Paul Breimyer, Guruprasad Kora, Chongle Pan, Srikanth B. Yoginath:
Scientific Data Analysis. Scientific Data Management 2009 - [r1]Ying Zhao, George Karypis:
Document Clustering. Encyclopedia of Database Systems 2009: 933-937 - 2008
- [j46]Nikil Wale, Ian A. Watson, George Karypis:
Indirect Similarity Based Methods for Effective Scaffold-Hopping in Chemical Compounds. J. Chem. Inf. Model. 48(4): 730-741 (2008) - [j45]Nikil Wale, Ian A. Watson, George Karypis:
Comparison of descriptor spaces for chemical compound retrieval and classification. Knowl. Inf. Syst. 14(3): 347-375 (2008) - [j44]Al Mamunur Rashid, George Karypis, John Riedl:
Learning preferences of new users in recommender systems: an information theoretic approach. SIGKDD Explor. 10(2): 90-100 (2008) - [j43]Mohammed J. Zaki, George Karypis, Jiong Yang, Wei Wang:
Introduction to special issue on bioinformatics. ACM Trans. Knowl. Discov. Data 2(1): 1:1 (2008) - [c92]Huzefa Rangwala, George Karypis:
fRMSDAlign: Protein Sequence Alignment Using Predicted Local Structure Information for Pairs with Low Sequence Identity. APBC 2008: 111-122 - [c91]Ruinan Zhang, Huzefa Rangwala, George Karypis:
Genome Alignments Using MPI-LAGAN. BIBM 2008: 437-440 - [c90]Irene Moulitsas, George Karypis:
Architecture Aware Partitioning Algorithms. ICA3PP 2008: 42-53 - [c89]Xia Ning, George Karypis:
The Set Classification Problem and Solution Methods. ICDM Workshops 2008: 720-729 - [c88]Rezwan Ahmed, Huzefa Rangwala, George Karypis:
TOPTMH: Topology Predictor for Transmembrane alpha-Helices. ECML/PKDD (1) 2008: 23-38 - [c87]Christopher Kauffman, George Karypis:
An Analysis of Information Content Present in Protein-DNA Interactions. Pacific Symposium on Biocomputing 2008: 477-488 - 2007
- [j42]Mohammed J. Zaki, George Karypis, Jiong Yang:
Data Mining in Bioinformatics (BIOKDD). Algorithms Mol. Biol. 2 (2007) - [j41]Huzefa Rangwala, George Karypis:
Incremental window-based protein sequence alignment algorithms. Bioinform. 23(2): 17-23 (2007) - [j40]Michihiro Kuramochi, George Karypis:
Discovering frequent geometric subgraphs. Inf. Syst. 32(8): 1101-1120 (2007) - [j39]Kevin W. DeRonne, George Karypis:
Effective Optimization Algorithms for Fragment-Assembly Based protein Structure Prediction. J. Bioinform. Comput. Biol. 5(2a): 335-352 (2007) - [j38]Ronald N. Kostoff, J. Antonio del Río, Héctor D. Cortés, Charles Smith, Andrew Smith, Caroline S. Wagner, Loet Leydesdorff, George Karypis, Guido Malpohl, Rene Tshiteya:
Clustering methodologies for identifying country core competencies. J. Inf. Sci. 33(1): 21-40 (2007) - [j37]Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis:
Out-of-core coherent closed quasi-clique mining from large dense graph databases. ACM Trans. Database Syst. 32(2): 13 (2007) - [c86]Steven P. Reinhardt, George Karypis:
A Multi-Level Parallel Implementation of a Program for Finding Frequent Patterns in a Large Sparse Graph. IPDPS 2007: 1-8 - [c85]Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal:
Discriminating Subsequence Discovery for Sequence Clustering. SDM 2007: 605-610 - 2006
- [j36]Huzefa Rangwala, George Karypis:
Building multiclass classifiers for remote homology detection and fold recognition. BMC Bioinform. 7: 455 (2006) - [j35]Jianyong Wang, George Karypis:
On efficiently summarizing categorical databases. Knowl. Inf. Syst. 9(1): 19-37 (2006) - [j34]Mohammed J. Zaki, George Karypis, Jiong Yang:
BIOKDD06: data mining in Bioinformatics. SIGKDD Explor. 8(2): 78 (2006) - [j33]Navaratnasothie Selvakkumaran, George Karypis:
Multiobjective hypergraph-partitioning algorithms for cut and maximum subdomain-degree minimization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 25(3): 504-517 (2006) - [j32]Jianyong Wang, George Karypis:
On Mining Instance-Centric Classification Rules. IEEE Trans. Knowl. Data Eng. 18(11): 1497-1511 (2006) - [c84]Nikil Wale, George Karypis:
Comparison of Descriptor Spaces for Chemical Compound Retrieval and Classification. ICDM 2006: 678-689 - [c83]Amine Abou-Rjeili, George Karypis:
Multilevel algorithms for partitioning power-law graphs. IPDPS 2006 - [c82]Al Mamunur Rashid, Shyong K. Lam, Adam LaPitz, George Karypis, John Riedl:
Towards a Scalable k NN CF Algorithm: Exploring Effective Applications of Clustering. WEBKDD 2006: 147-166 - [c81]Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis:
Coherent closed quasi-clique discovery from large dense graph databases. KDD 2006: 797-802 - [p3]Ying Zhao, George Karypis:
Criterion Functions for Clustering on High-Dimensional Data. Grouping Multidimensional Data 2006: 211-237 - [p2]Karen D. Devine, Erik G. Boman, George Karypis:
Partitioning and Load Balancing for Emerging Parallel Applications and Architectures. Parallel Processing for Scientific Computing 2006: 99-126 - 2005
- [j31]Huzefa Rangwala, George Karypis:
Profile-based direct kernels for remote homology detection and fold recognition. Bioinform. 21(23): 4239-4247 (2005) - [j30]Ying Zhao, George Karypis, Usama M. Fayyad:
Hierarchical Clustering Algorithms for Document Datasets. Data Min. Knowl. Discov. 10(2): 141-168 (2005) - [j29]Masakazu Seno, George Karypis:
Finding Frequent Patterns Using Length-Decreasing Support Constraints. Data Min. Knowl. Discov. 10(3): 197-228 (2005) - [j28]Michihiro Kuramochi, George Karypis:
Finding Frequent Patterns in a Large Sparse Graph*. Data Min. Knowl. Discov. 11(3): 243-271 (2005) - [j27]Michihiro Kuramochi, George Karypis:
Gene Classification Using Expression Profiles: A Feasibility Study. Int. J. Artif. Intell. Tools 14(4): 641-660 (2005) - [j26]Ying Zhao, George Karypis:
Prediction of Contact Maps Using Support Vector Machines. Int. J. Artif. Intell. Tools 14(5): 849-866 (2005) - [j25]Mukund Deshpande, Michihiro Kuramochi, Nikil Wale, George Karypis:
Frequent Substructure-Based Approaches for Classifying Chemical Compounds. IEEE Trans. Knowl. Data Eng. 17(8): 1036-1050 (2005) - [c80]Benjamin W. Mayer, Huzefa Rangwala, Rohit Gupta, Jaideep Srivastava, George Karypis, Vipin Kumar, Piet C. de Groen:
Feature Mining for Prediction of Degree of Liver Fibrosis. AMIA 2005 - [c79]Eui-Hong Han, George Karypis:
Feature-based recommendation system. CIKM 2005: 446-452 - [c78]Jack G. Conrad, Khalid Al-Kofahi, Ying Zhao, George Karypis:
Effective Document Clustering for Large Heterogeneous Law Firm Collections. ICAIL 2005: 177-187 - [c77]Jianyong Wang, George Karypis:
HARMONY: Efficiently Mining the Best Rules for Classification. SDM 2005: 205-216 - [c76]Ying Zhao, George Karypis:
Topic-driven Clustering for Document Datasets. SDM 2005: 358-369 - [c75]Al Mamunur Rashid, George Karypis, John Riedl:
Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach. SDM 2005: 556-560 - [p1]Mukund Deshpande, Michihiro Kuramochi, George Karypis:
Mining Chemical Compounds. Data Mining in Bioinformatics 2005: 189-215 - 2004
- [j24]Ying Zhao, George Karypis:
Empirical and Theoretical Comparisons of Selected Criterion Functions for Document Clustering. Mach. Learn. 55(3): 311-331 (2004) - [j23]Valerie Guralnik, George Karypis:
Parallel tree-projection-based sequence mining algorithms. Parallel Comput. 30(4): 443-472 (2004) - [j22]Michihiro Kuramochi, George Karypis:
An Efficient Algorithm for Discovering Frequent Subgraphs. IEEE Trans. Knowl. Data Eng. 16(9): 1038-1051 (2004) - [j21]Mukund Deshpande, George Karypis:
Item-based top-N recommendation algorithms. ACM Trans. Inf. Syst. 22(1): 143-177 (2004) - [j20]Mukund Deshpande, George Karypis:
Selective Markov models for predicting Web page accesses. ACM Trans. Internet Techn. 4(2): 163-184 (2004) - [c74]Ying Zhao, George Karypis:
Soft clustering criterion functions for partitional document clustering: a summary of results. CIKM 2004: 246-247 - [c73]Navaratnasothie Selvakkumaran, Abhishek Ranjan, Salil Raje, George Karypis:
Multi-resource aware partitioning algorithms for FPGAs with heterogeneous resources. DAC 2004: 741-746 - [c72]Navaratnasothie Selvakkumaran, Abhishek Ranjan, Salil Raje, George Karypis:
Multi-resource aware partitioning algorithms for FPGAs with heterogeneous resources. FPGA 2004: 253 - [c71]Jianyong Wang, George Karypis:
SUMMARY: Efficiently Summarizing Transactions for Clustering. ICDM 2004: 241-248 - [c70]Michihiro Kuramochi, George Karypis:
GREW-A Scalable Frequent Subgraph Discovery Algorithm. ICDM 2004: 439-442 - [c69]Krishna Gade, Jianyong Wang, George Karypis:
Efficient closed pattern mining in the presence of tough block constraints. KDD 2004: 138-147 - [c68]Michihiro Kuramochi, George Karypis:
Finding Frequent Patterns in a Large Sparse Graph. SDM 2004: 345-356 - [c67]Jianyong Wang, George Karypis:
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint. SDM 2004: 432-436 - 2003
- [j19]Daniel J. Challou, Maria L. Gini, Vipin Kumar, George Karypis:
Predicting the Performance of Randomized Parallel Search: An Application to Robot Motion Planning. J. Intell. Robotic Syst. 38(1): 31-53 (2003) - [c66]Ying Zhao, George Karypis:
Prediction of Contact Maps Using Support Vector Machines. BIBE 2003: 26- - [c65]Eui-Hong Han, George Karypis, Doug Mewhort, Keith Hatchard:
Intelligent metasearch engine for knowledge management. CIKM 2003: 492-495 - [c64]Navaratnasothie Selvakkumaran, George Karypis:
Multi.Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization. ICCAD 2003: 726-733 - [c63]Mukund Deshpande, Michihiro Kuramochi, George Karypis:
Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds. ICDM 2003: 35-42 - [c62]George Karypis:
Multi-Constraint Mesh Partitioning for Contact/Impact Computations. SC 2003: 56 - [c61]Navaratnasothie Selvakkumaran, Phiroze N. Parakh, George Karypis:
Perimeter-degree: a priori metric for directly measuring and homogenizing interconnection complexity in multilevel placement. SLIP 2003: 53-59 - 2002
- [j18]Kirk Schloegel, George Karypis, Vipin Kumar:
Parallel static and dynamic multi-constraint graph partitioning. Concurr. Comput. Pract. Exp. 14(3): 219-240 (2002) - [c60]Mukund Deshpande, George Karypis:
Using conjunction of attribute values for classification. CIKM 2002: 356-364 - [c59]Ying Zhao, George Karypis:
Evaluation of hierarchical clustering algorithms for document datasets. CIKM 2002: 515-524 - [c58]Cristinel Ababei, Navaratnasothie Selvakkumaran, Kia Bazargan, George Karypis:
Multi-objective circuit partitioning for cutsize and path-based delay minimization. ICCAD 2002: 181-185 - [c57]Michihiro Kuramochi, George Karypis:
Discovering Frequent Geometric Subgraphs. ICDM 2002: 258-265 - [c56]Masakazu Seno, George Karypis:
SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint. ICDM 2002: 418-425 - [c55]Jian Liu, Ying Zhao, Eugene Shragowitz, George Karypis:
A polynomial time approximation scheme for rectilinear Steiner minimum tree construction in the presence of obstacles. ICECS 2002: 781-784 - [c54]Ying Zhao, George Karypis:
Improve Precategorized Collection Retrieval by Using Supervised Term Weighting Schemes. ITCC 2002: 16-21 - [c53]Mukund Deshpande, Michihiro Kuramochi, George Karypis:
Automated Approaches for Classifying Structures. BIOKDD 2002: 11-18 - [c52]Mukund Deshpande, George Karypis:
Evaluation of Techniques for Classifying Biological Sequences. PAKDD 2002: 417-431 - [c51]B. Uygar Oztekin, George Karypis, Vipin Kumar:
Expert agreement and content based reranking in a meta search environment using Mearf. WWW 2002: 333-344 - 2001
- [j17]Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Grama, George Karypis:
Privacy Risks in Recommender Systems. IEEE Internet Comput. 5(6): 54-62 (2001) - [j16]Kirk Schloegel, George Karypis, Vipin Kumar:
Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes. IEEE Trans. Parallel Distributed Syst. 12(5): 451-466 (2001) - [c50]Michihiro Kuramochi, George Karypis:
Gene Classification using Expression Profiles: A Feasibility Study. BIBE 2001: 191-200 - [c49]George Karypis:
Evaluation of Item-Based Top-N Recommendation Algorithms. CIKM 2001: 247-254 - [c48]Kirk Schloegel, George Karypis, Vipin Kumar:
Graph Partitioning for Dynamic, Adaptive and Multi-phase Scientific Simulations. CLUSTER 2001: 271-273 - [c47]Valerie Guralnik, Nivea Garg, George Karypis:
Parallel Tree Projection Algorithm for Sequence Mining. Euro-Par 2001: 310-320 - [c46]Valerie Guralnik, George Karypis:
A Scalable Algorithm for Clustering Sequential Data. ICDM 2001: 179-186 - [c45]Michihiro Kuramochi, George Karypis:
Frequent Subgraph Discovery. ICDM 2001: 313-320 - [c44]Masakazu Seno, George Karypis:
LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint. ICDM 2001: 505-512 - [c43]Valerie Guralnik, George Karypis:
A scalable algorithm for clustering protein sequences. BIOKDD 2001: 73-80 - [c42]Eui-Hong Han, George Karypis, Vipin Kumar:
Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification. PAKDD 2001: 53-65 - [c41]Irene Moulitsas, George Karypis:
Multilevel algorithms for generating coarse grids for multigrid methods. SC 2001: 45 - [c40]Mukund Deshpande, George Karypis:
Selective Markov Models for Predicting Web-Page Accesses. SDM 2001: 1-15 - [c39]Badrul Munir Sarwar, George Karypis, Joseph A. Konstan, John Riedl:
Item-based collaborative filtering recommendation algorithms. WWW 2001: 285-295 - [i1]Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Grama, George Karypis:
When being Weak is Brave: Privacy in Recommender Systems. CoRR cs.CG/0105028 (2001) - 2000
- [j15]Rupak Biswas, Bruce Hendrickson, George Karypis:
Graph partitioning and parallel computing. Parallel Comput. 26(12): 1515-1517 (2000) - [j14]Eui-Hong Han, George Karypis, Vipin Kumar:
Scalable Parallel Data Mining for Association Rules. IEEE Trans. Knowl. Data Eng. 12(3): 377-352 (2000) - [j13]George Karypis, Vipin Kumar:
Multilevel k-way Hypergraph Partitioning. VLSI Design 11(3): 285-300 (2000) - [c38]Eui-Hong Han, George Karypis:
Fast Supervised Dimensionality Reduction Algorithm with Applications to Document Categorization & Retrieval. CIKM 2000: 12-19 - [c37]William Leinberger, George Karypis, Vipin Kumar:
Memory Management Techniques for Gang Scheduling. Euro-Par 2000: 252-261 - [c36]Kirk Schloegel, George Karypis, Vipin Kumar:
Parallel Multilevel Algorithms for Multi-constraint Graph Partitioning (Distinguished Paper). Euro-Par 2000: 296-310 - [c35]William Leinberger, George Karypis, Vipin Kumar:
Load Balancing Across Near-Homogeneous Multi-Resource Servers. Heterogeneous Computing Workshop 2000: 60-71 - [c34]Vipin Kumar, Kirk Schloegel, George Karypis:
Graph Partitioning for Dynamic, Adaptive, and Multi-phase Computations. IPDPS Workshops 2000: 476-476 - [c33]Eui-Hong Han, George Karypis:
Centroid-Based Document Classification: Analysis and Experimental Results. PKDD 2000: 424-431 - [c32]Kirk Schloegel, George Karypis, Vipin Kumar:
A Unified Algorithm for Load-balancing Adaptive Scientific Simulations. SC 2000: 59 - [c31]Badrul Munir Sarwar, George Karypis, Joseph A. Konstan, John Riedl:
Analysis of recommendation algorithms for e-commerce. EC 2000: 158-167
1990 – 1999
- 1999
- [j12]Daniel Boley, Maria L. Gini, Robert Gross, Eui-Hong Han, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
Document Categorization and Query Generation on the World Wide Web Using WebACE. Artif. Intell. Rev. 13(5-6): 365-391 (1999) - [j11]George Karypis, Eui-Hong Han, Vipin Kumar:
Chameleon: Hierarchical Clustering Using Dynamic Modeling. Computer 32(8): 68-75 (1999) - [j10]Daniel Boley, Maria L. Gini, Robert Gross, Eui-Hong Han, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
Partitioning-based clustering for Web document categorization. Decis. Support Syst. 27(3): 329-341 (1999) - [j9]George Karypis, Vipin Kumar:
Parallel Multilevel series k-Way Partitioning Scheme for Irregular Graphs. SIAM Rev. 41(2): 278-300 (1999) - [j8]George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar:
Multilevel hypergraph partitioning: applications in VLSI domain. IEEE Trans. Very Large Scale Integr. Syst. 7(1): 69-79 (1999) - [c30]George Karypis, Vipin Kumar:
Multilevel k-way Hypergraph Partitioning. DAC 1999: 343-348 - [c29]Kirk Schloegel, George Karypis, Vipin Kumar:
A New Algorithm for Multi-objective Graph Partitioning. Euro-Par 1999: 322-331 - [c28]William Leinberger, George Karypis, Vipin Kumar:
Multi-Capacity Bin Packing Algorithms with Applications to Job Scheduling under Multiple Constraints. ICPP 1999: 404-412 - [c27]Mahesh V. Joshi, Eui-Hong Han, George Karypis, Vipin Kumar:
Efficient Parallel Algorithms for Mining Associations. Large-Scale Parallel Data Mining 1999: 83-126 - [c26]Mahesh V. Joshi, George Karypis, Vipin Kumar, Anshul Gupta, Fred G. Gustavson:
PSPASES: An Efficient and Scalable Parallel Sparse Direct Solver. PP 1999 - [c25]Kirk Schloegel, George Karypis, Vipin Kumar:
Dynamic Repartitioning of Adaptively Refined Meshes. PP 1999 - [c24]William Leinberger, George Karypis, Vipin Kumar:
Job Scheduling in the presence of Multiple Resource Requirements. SC 1999: 47 - 1998
- [j7]Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher:
Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results. IEEE Data Eng. Bull. 21(1): 15-22 (1998) - [j6]George Karypis, Vipin Kumar:
A Parallel Algorithm for Multilevel Graph Partitioning and Sparse Matrix Ordering. J. Parallel Distributed Comput. 48(1): 71-95 (1998) - [j5]George Karypis, Vipin Kumar:
Multilevel k-way Partitioning Scheme for Irregular Graphs. J. Parallel Distributed Comput. 48(1): 96-129 (1998) - [j4]George Karypis, Vipin Kumar:
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs. SIAM J. Sci. Comput. 20(1): 359-392 (1998) - [c23]Eui-Hong Han, Daniel Boley, Maria L. Gini, Robert Gross, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
WebACE: A Web Agent for Document Categorization and Exploration. Agents 1998: 408-415 - [c22]Mahesh V. Joshi, George Karypis, Vipin Kumar:
ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets. IPPS/SPDP 1998: 573-579 - [c21]George Karypis, Vipin Kumar:
Multilevel Algorithms for Multi-Constraint Graph Partitioning. SC 1998: 28 - [c20]Kirk Schloegel, George Karypis, Vipin Kumar:
Dynamic Repartitioning of Adaptively Refined Meshes. SC 1998: 29 - [c19]Kirk Schloegel, George Karypis, Vipin Kumar:
Load Balancing of Dynamic and Adaptive Mesh-Based Computations. SRDS 1998: 311 - 1997
- [j3]Kirk Schloegel, George Karypis, Vipin Kumar:
Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes. J. Parallel Distributed Comput. 47(2): 109-124 (1997) - [j2]Anshul Gupta, George Karypis, Vipin Kumar:
Highly Scalable Parallel Algorithms for Sparse Matrix Factorization. IEEE Trans. Parallel Distributed Syst. 8(5): 502-520 (1997) - [c18]George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar:
Multilevel Hypergraph Partitioning: Application in VLSI Domain. DAC 1997: 526-529 - [c17]Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher:
Clustering Based On Association Rule Hypergraphs. DMKD 1997 - [c16]Kirk Schloegel, George Karypis, Vipin Kumar:
Repartitioning of Adaptive Meshes: Experiments with Multilevel Diffusion. Euro-Par 1997: 945-949 - [c15]Mahesh V. Joshi, Anshul Gupta, George Karypis, Vipin Kumar:
A high performance two dimensional scalable parallel algorithm for solving sparse triangular systems. HiPC 1997: 137-143 - [c14]Anshul Gupta, Fred G. Gustavson, Mahesh V. Joshi, George Karypis, Vipin Kumar:
Design and Implementation of a Scalable Parallel Direct Solver for Sparse Symmetric Positive Definite Systems: Preliminary Results. PP 1997 - [c13]George Karypis, Vipin Kumar:
A Coarse-Grain Parallel Formulation of Multilevel k-way Graph Partitioning Algorithm. PP 1997 - [c12]Vipin Kumar, George Karypis, Ananth Grama:
Role of Message-Passing in Performance Oriented Parallel Programming. PP 1997 - [c11]George Karypis, Vipin Kumar:
Parallel Threshold-based ILU Factorization. SC 1997: 28 - [c10]Eui-Hong Han, George Karypis, Vipin Kumar:
Scalable Parallel Data Mining for Association Rules. SIGMOD Conference 1997: 277-288 - 1996
- [c9]George Karypis, Vipin Kumar:
Parallel Multilevel Graph Partitioning. IPPS 1996: 314-319 - [c8]George Karypis, Vipin Kumar:
Parallel Multilevel k-way Partitioning Scheme for Irregular Graphs. SC 1996: 35 - 1995
- [c7]George Karypis, Vipin Kumar:
Multilevel Graph Partitioning Schemes. ICPP (3) 1995: 113-122 - [c6]George Karypis, Anshul Gupta, Vipin Kumar:
A Highly Parallel Interior Point Algorithm. PP 1995: 110-112 - [c5]George Karypis, Vipin Kumar:
Analysis of Multilevel Graph Partitioning. SC 1995: 29 - 1994
- [b1]Vipin Kumar, Ananth Grama, Anshul Gupta, George Karypis:
Introduction to Parallel Computing. Benjamin/Cummings 1994, ISBN 0-8053-3170-0 - [j1]George Karypis, Vipin Kumar:
Unstructured Tree Search on SIMD Parallel Computers. IEEE Trans. Parallel Distributed Syst. 5(10): 1057-1072 (1994) - [c4]George Karypis, Anshul Gupta, Vipin Kumar:
Experiences with a Parallel Formulation of an Interior Point Algorithm. Parallel Processing of Discrete Optimization Problems 1994: 163-180 - [c3]George Karypis, Anshul Gupta, Vipin Kumar:
A parallel formulation of interior point algorithms. SC 1994: 204-213 - 1993
- [c2]George Karypis, Vipin Kumar:
Efficient Parallel Mappings of a Dynamic Programming Algorithm: A Summary of Results. IPPS 1993: 563-568 - 1992
- [c1]George Karypis, Vipin Kumar:
Unstructured Tree Search on SIMD Parallel Computers: A Summary of Results. SC 1992: 453-462
Coauthor Index
[e10] [p4] [c80] [j19] [j18] [c51] [j16] [c48] [c42] [j14] [j13] [c37] [c36] [c35] [c34] [c32] [j12] [j11] [j10] [j9] [j8] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [j7] [j6] [j5] [j4] [c23] [c22] [c21] [c20] [c19] [j3] [j2] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [b1] [j1] [c4] [c3] [c2] [c1]
Dominique LaSalle
aka: Dominique Lasalle
aka: Dominique Lasalle
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