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ORCIDHuzefa Rangwala
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- affiliation: George Mason University, Fairfax VA, USA
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2020 – today
- 2024
[c134]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- [c133]Yuze Lou, Chuan Lei, Xiao Qin, Zichen Wang, Christos Faloutsos, Rishita Anubhai, Huzefa Rangwala:
DATALORE: Can a Large Language Model Find All Lost Scrolls in a Data Repository? ICDE 2024: 5170-5176 - [c132]Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai:
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs. ICLR 2024 - [c131]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 - [c130]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 - [c129]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 - [i47]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) - [i46]Jonathan Vasquez, Carlotta Domeniconi, Huzefa Rangwala:
DispaRisk: Assessing and Interpreting Disparity Risks in Datasets. CoRR abs/2405.12372 (2024) - [i45]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) - [i44]Jiaming Liang, Chuan Lei, Xiao Qin, Jiani Zhang, Asterios Katsifodimos, Christos Faloutsos, Huzefa Rangwala:
FeatNavigator: Automatic Feature Augmentation on Tabular Data. CoRR abs/2406.09534 (2024) - [i43]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) - [i42]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) - [i41]Xiaoxue Han, Huzefa Rangwala, Yue Ning:
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification. CoRR abs/2410.20295 (2024) - [i40]Zihan Pengmei, Zhengyuan Shen, Zichen Wang, Marcus Collins, Huzefa Rangwala:
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer. CoRR abs/2410.21683 (2024) - 2023
- [j29]Panneer Selvam Santhalingam, Parth Pathak, Huzefa Rangwala, Jana Kosecka:
Synthetic Smartwatch IMU Data Generation from In-the-wild ASL Videos. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7(2): 74:1-74:34 (2023) - [c128]Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Sanmay Das:
Counterfactually Fair Dynamic Assignment: A Case Study on Policing. AAMAS 2023: 2526-2528 - [c127]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. EMNLP 2023: 13276-13290 - [c126]Mia C. Mayer, Muhammad Bilal Zafar, Luca Franceschi, Huzefa Rangwala:
Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". KDD 2023: 5783-5785 - [c125]Jonathan Vasquez, Xavier Gitiaux, Huzefa Rangwala:
Estimating the Risk of Individual Discrimination of Classifiers. PAKDD (1) 2023: 495-506 - [e3]M. Emre Celebi, Md Sirajus Salekin, Hyunwoo J. Kim, Shadi Albarqouni, Catarina Barata, Allan Halpern, Philipp Tschandl, Marc Combalia, Yuan Liu, Ghada Zamzmi, Joshua Levy, Huzefa Rangwala, Annika Reinke, Diya Wynn, Bennett A. Landman, Won-Ki Jeong, Yiqing Shen, Zhongying Deng, Spyridon Bakas, Xiaoxiao Li, Chen Qin, Nicola Rieke, Holger Roth, Daguang Xu:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops - ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings. Lecture Notes in Computer Science 14393, Springer 2023, ISBN 978-3-031-47400-2 [contents] - [i39]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) - [i38]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. CoRR abs/2310.13196 (2023) - [i37]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) - 2022
- [c124]Angeela Acharya, Siddhartha Sikdar, Sanmay Das, Huzefa Rangwala:
GenSyn: A Multi-stage Framework for Generating Synthetic Microdata using Macro Data Sources. IEEE Big Data 2022: 685-692 - [c123]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala:
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam. IEEE Big Data 2022: 1850-1857 - [c122]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CASE@EMNLP 2022: 32-43 - [c121]Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick J. Fowler, Sanmay Das:
Trade-offs between Group Fairness Metrics in Societal Resource Allocation. FAccT 2022: 1095-1105 - [c120]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning. ICDM 2022: 91-100 - [c119]Xavier Gitiaux, Huzefa Rangwala:
SoFaiR: Single Shot Fair Representation Learning. IJCAI 2022: 687-695 - [c118]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Robust Event Forecasting with Spatiotemporal Confounder Learning. KDD 2022: 294-304 - [c117]Zichen Wang, Vassilis N. Ioannidis, Huzefa Rangwala, Tatsuya Arai, Ryan Brand, Mufei Li, Yohei Nakayama:
Graph Neural Networks in Life Sciences: Opportunities and Solutions. KDD 2022: 4834-4835 - [c116]Jonathan Vasquez Verdugo, Xavier Gitiaux, Cesar Ortega, Huzefa Rangwala:
FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context. LAK 2022: 271-281 - [e2]Aidong Zhang, Huzefa Rangwala:
KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM 2022, ISBN 978-1-4503-9385-0 [contents] - [i36]Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick J. Fowler, Sanmay Das:
Trade-offs between Group Fairness Metrics in Societal Resource Allocation. CoRR abs/2202.12334 (2022) - [i35]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CoRR abs/2204.02531 (2022) - [i34]Xavier Gitiaux, Huzefa Rangwala:
SoFaiR: Single Shot Fair Representation Learning. CoRR abs/2204.12556 (2022) - [i33]Jonathan Vasquez Verdugo, Xavier Gitiaux, Huzefa Rangwala:
Ex-Ante Assessment of Discrimination in Dataset. CoRR abs/2208.07918 (2022) - [i32]Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala, Layne Price:
Training self-supervised peptide sequence models on artificially chopped proteins. CoRR abs/2211.06428 (2022) - [i31]Angeela Acharya, Siddhartha Sikdar, Sanmay Das, Huzefa Rangwala:
GenSyn: A Multi-stage Framework for Generating Synthetic Microdata using Macro Data Sources. CoRR abs/2212.05975 (2022) - 2021
- [c115]Xavier Gitiaux, Huzefa Rangwala:
Fair Representations by Compression. AAAI 2021: 11506-11515 - [c114]Xavier Gitiaux, Huzefa Rangwala:
Learning Smooth and Fair Representations. AISTATS 2021: 253-261 - [c113]Hui Zheng, Pattiya Mahapasuthanon, Yujing Chen, Huzefa Rangwala, Anya S. Evmenova, Vivian Genaro Motti:
WLA4ND: a Wearable Dataset of Learning Activities for Young Adults with Neurodiversity to Provide Support in Education. ASSETS 2021: 29:1-29:15 - [c112]Al Amin Hosain, Huzefa Rangwala, Jana Kosecká:
Improving Sign Video Modeling Using Graph Neural Network. IEEE BigData 2021: 4506-4513 - [c111]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. IEEE BigData 2021: 4822-4831 - [c110]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Understanding Event Predictions via Contextualized Multilevel Feature Learning. CIKM 2021: 342-351 - [c109]Anlan Du, Alexandra Plukis, Huzefa Rangwala:
Using Course Evaluations and Student Data to Predict Computer Science Student Success. EDM (Workshops) 2021 - [c108]Dom Huh, Huzefa Rangwala:
Synthetic Embedding-based Data Generation Methods for Student Performance. EDM (Workshops) 2021 - [c107]Ashish Hingle, Huzefa Rangwala, Aditya Johri, Alex Monea:
Using Role-Plays to Improve Ethical Understanding of Algorithms Among Computing Students. FIE 2021: 1-7 - [c106]Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers. SC 2021: 60 - [c105]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecká:
Hand Pose Guided 3D Pooling for Word-level Sign Language Recognition. WACV 2021: 3428-3438 - [i30]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala:
Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling. CoRR abs/2103.07792 (2021) - [i29]Xavier Gitiaux, Huzefa Rangwala:
Fair Representations by Compression. CoRR abs/2105.14044 (2021) - [i28]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala:
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam. CoRR abs/2108.13620 (2021) - [i27]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. CoRR abs/2109.00151 (2021) - [i26]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causal Knowledge Guided Societal Event Forecasting. CoRR abs/2112.05695 (2021) - 2020
- [j28]Mohammad Arifur Rahman, Huzefa Rangwala:
IDMIL: an alignment-free Interpretable Deep Multiple Instance Learning (MIL) for predicting disease from whole-metagenomic data. Bioinform. 36(Supplement-1): i39-i47 (2020) - [j27]Panneer Selvam Santhalingam, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar:
mmASL: Environment-Independent ASL Gesture Recognition Using 60 GHz Millimeter-wave Signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(1): 26:1-26:30 (2020) - [j26]Mohammad Arifur Rahman, Nathan LaPierre, Huzefa Rangwala:
Phenotype Prediction from Metagenomic Data Using Clustering and Assembly with Multiple Instance Learning (CAMIL). IEEE ACM Trans. Comput. Biol. Bioinform. 17(3): 828-840 (2020) - [c104]Yuanqi Du, Nguyen Dang, Riley Wilkerson, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka:
American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract). AAAI 2020: 13781-13782 - [c103]Jitin Krishnan, Patrick Coronado, Hemant Purohit, Huzefa Rangwala:
Common-Knowledge Concept Recognition for SEVA. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1) 2020 - [c102]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency Services. ASONAM 2020: 409-416 - [c101]Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. IEEE BigData 2020: 15-24 - [c100]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning:
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. CIKM 2020: 245-254 - [c99]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecká, Huzefa Rangwala:
Body Pose and Deep Hand-shape Feature Based American Sign Language Recognition. DSAA 2020: 207-215 - [c98]Qian Hu, Huzefa Rangwala:
Towards Fair Educational Data Mining: A Case Study on Detecting At-risk Students. EDM 2020 - [c97]Noah Hunt-Isaak, Peter Cherniavsky, Mark Snyder, Huzefa Rangwala:
Using online text books and in-class quizzes to predict in class performance. EDM 2020 - [c96]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecká:
FineHand: Learning Hand Shapes for American Sign Language Recognition. FG 2020: 700-707 - [c95]Qian Hu, Huzefa Rangwala:
Metric-Free Individual Fairness with Cooperative Contextual Bandits. ICDM 2020: 182-191 - [c94]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Learning with Hierarchical Attention for Sensor Data Analytics. IJCNN 2020: 1-8 - [c93]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Attention Realignment and Pseudo-Labelling for Interpretable Cross-Lingual Classification of Crisis Tweets. KiML@KDD 2020: 43-50 - [c92]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Dynamic Knowledge Graph based Multi-Event Forecasting. KDD 2020: 1585-1595 - [c91]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Diversity-Based Generalization for Unsupervised Text Classification Under Domain Shift. ECML/PKDD (2) 2020: 657-672 - [c90]Angeela Acharya, Jitin Krishnan, Desmond Arias, Huzefa Rangwala:
Homicidal Event Forecasting and Interpretable Analysis Using Hierarchical Attention Model. SBP-BRiMS 2020: 140-150 - [c89]Panneer Selvam Santhalingam, Yuanqi Du, Riley Wilkerson, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar:
Expressive ASL Recognition using Millimeter-wave Wireless Signals. SECON 2020: 1-9 - [i25]Qian Hu, Huzefa Rangwala:
Academic Performance Estimation with Attention-based Graph Convolutional Networks. CoRR abs/2001.00632 (2020) - [i24]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Diversity-Based Generalization for Neural Unsupervised Text Classification under Domain Shift. CoRR abs/2002.10937 (2020) - [i23]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Social Web Data for Emergency Services. CoRR abs/2003.04991 (2020) - [i22]Dom Huh, Sai Gurrapu, Frederick Olson, Huzefa Rangwala, Parth H. Pathak, Jana Kosecka:
Generative Multi-Stream Architecture For American Sign Language Recognition. CoRR abs/2003.08743 (2020) - [i21]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka:
FineHand: Learning Hand Shapes for American Sign Language Recognition. CoRR abs/2003.08753 (2020) - [i20]Jitin Krishnan, Patrick Coronado, Hemant Purohit, Huzefa Rangwala:
Common-Knowledge Concept Recognition for SEVA. CoRR abs/2003.11687 (2020) - [i19]Xavier Gitiaux, Huzefa Rangwala:
Learning Smooth and Fair Representations. CoRR abs/2006.08788 (2020) - [i18]Zheng Chai, Yujing Chen, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data. CoRR abs/2010.05958 (2020) - [i17]Qian Hu, Huzefa Rangwala:
Metric-Free Individual Fairness with Cooperative Contextual Bandits. CoRR abs/2011.06738 (2020)
2010 – 2019
- 2019
- [j25]Carrie Klein, Jaime Lester, Huzefa Rangwala, Aditya Johri:
Technological barriers and incentives to learning analytics adoption in higher education: insights from users. J. Comput. High. Educ. 31(3): 604-625 (2019) - [j24]Azad Naik, Huzefa Rangwala:
Improving large-scale hierarchical classification by rewiring: a data-driven filter based approach. J. Intell. Inf. Syst. 52(1): 141-164 (2019) - [c88]Yujing Chen, Huzefa Rangwala:
Attention-based Multi-task Learning for Sensor Analytics. IEEE BigData 2019: 2187-2196 - [c87]Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala:
Grade Prediction with Neural Collaborative Filtering. DSAA 2019: 1-10 - [c86]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecká, Huzefa Rangwala:
Sign Language Recognition Analysis using Multimodal Data. DSAA 2019: 203-210 - [c85]Qian Hu, Huzefa Rangwala:
Academic Performance Estimation with Attention-based Graph Convolutional Networks. EDM 2019 - [c84]Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala:
Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. EDM 2019 - [c83]Justin Alvin, Bob Kurtz, Paul Ammann, Huzefa Rangwala, René Just:
Guiding testing effort using mutant utility. ICSE (Companion Volume) 2019: 312-313 - [c82]Xavier Gitiaux, Huzefa Rangwala:
mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers. IJCAI 2019: 5871-5879 - [c81]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Learning Dynamic Context Graphs for Predicting Social Events. KDD 2019: 1007-1016 - [c80]Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala:
Spatio-temporal Event Forecasting and Precursor Identification. KDD 2019: 3237-3238 - [c79]David C. Anastasiu, Huzefa Rangwala, Andrea Tagarelli:
Tutorial: Are You My Neighbor?: Bringing Order to Neighbor Computing Problems. KDD 2019: 3241-3242 - [c78]Qian Hu, Huzefa Rangwala:
Reliable Deep Grade Prediction with Uncertainty Estimation. LAK 2019: 76-85 - [c77]Sneha Mehta, Mohammad Raihanul Islam, Huzefa Rangwala, Naren Ramakrishnan:
Event Detection using Hierarchical Multi-Aspect Attention. WWW 2019: 3079-3085 - [i16]Qian Hu, Huzefa Rangwala:
Reliable Deep Grade Prediction with Uncertainty Estimation. CoRR abs/1902.10213 (2019) - [i15]Xavier Gitiaux, Huzefa Rangwala:
Multi-Differential Fairness Auditor for Black Box Classifiers. CoRR abs/1903.07609 (2019) - [i14]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Hierarchical Attention Model for Sensor Analytics. CoRR abs/1905.05142 (2019) - [i13]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecka, Huzefa Rangwala:
Sign Language Recognition Analysis using Multimodal Data. CoRR abs/1909.11232 (2019) - [i12]Yujing Chen, Yue Ning, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices. CoRR abs/1911.02134 (2019) - [i11]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Low Rank Factorization for Compact Multi-Head Self-Attention. CoRR abs/1912.00835 (2019) - [i10]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning:
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction. CoRR abs/1912.10202 (2019) - 2018
- [b1]Azad Naik, Huzefa Rangwala:
Large Scale Hierarchical Classification: State of the Art. Springer Briefs in Computer Science, Springer 2018, ISBN 978-3-030-01619-7, pp. 1-93 - [j23]Omaima Almatrafi, Aditya Johri, Huzefa Rangwala:
Needle in a haystack: Identifying learner posts that require urgent response in MOOC discussion forums. Comput. Educ. 118: 1-9 (2018) - [c76]Li Zhang, Huzefa Rangwala:
Early Identification of At-Risk Students Using Iterative Logistic Regression. AIED (1) 2018: 613-626 - [c75]Yue Ning, Sathappan Muthiah, Naren Ramakrishnan, Huzefa Rangwala, David Mares:
When do Crowds Turn Violent? Uncovering Triggers from Media. ASONAM 2018: 77-82 - [c74]Mohammad Arifur Rahman, Huzefa Rangwala:
RegMIL: Phenotype Classification from Metagenomic Data. BCB 2018: 145-154 - [c73]Ananya S. Dhawan, Jana Kosecka, Huzefa Rangwala, Siddhartha Sikdar:
An intuitive muscle-computer interface using ultrasound sensing and Markovian state transitions. ISBI 2018: 1191-1194 - [c72]Yujing Chen, Aditya Johri, Huzefa Rangwala:
Running out of STEM: a comparative study across STEM majors of college students at-risk of dropping out early. LAK 2018: 270-279 - [c71]Qian Hu, Huzefa Rangwala:
Course-Specific Markovian Models for Grade Prediction. PAKDD (2) 2018: 29-41 - [c70]Nasrin Akhter, Liang Zhao, Desmond Arias, Huzefa Rangwala, Naren Ramakrishnan:
Forecasting Gang Homicides with Multi-level Multi-task Learning. SBP-BRiMS 2018: 28-37 - [c69]Sneha Nagpaul, Huzefa Rangwala:
From Language to Location Using Multiple Instance Neural Networks. SBP-BRiMS 2018: 46-53 - [c68]Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. SDM 2018: 99-107 - [c67]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
ALE: Additive Latent Effect Models for Grade Prediction. SDM 2018: 477-485 - [r1]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Relational Network Classification and Its Applications in Recommender Systems. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i9]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
ALE: Additive Latent Effect Models for Grade Prediction. CoRR abs/1801.05535 (2018) - 2017
- [j22]Azad Naik, Huzefa Rangwala:
HierFlat: flattened hierarchies for improving top-down hierarchical classification. Int. J. Data Sci. Anal. 4(3): 191-208 (2017) - [j21]Mohammad Arifur Rahman, Nathan Lapierre, Huzefa Rangwala, Daniel Barbará:
Metagenome sequence clustering with hash-based canopies. J. Bioinform. Comput. Biol. 15(6): 1740006:1-1740006:18 (2017) - [c66]Qian Hu, Agoritsa Polyzou, George Karypis, Huzefa Rangwala:
Enriching Course-Specific Regression Models with Content Features for Grade Prediction. DSAA 2017: 504-513 - [c65]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
Grade Prediction with Temporal Course-wise Influence. EDM 2017 - [c64]Qingzhe Li, Jessica Lin, Liang Zhao, Huzefa Rangwala:
A Uniform Representation for Trajectory Learning Tasks. SIGSPATIAL/GIS 2017: 80:1-80:4 - [c63]Yifeng Gao, Jessica Lin, Huzefa Rangwala:
IterativE Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. ICDM 2017: 111-116 - [c62]Azad Naik, Huzefa Rangwala:
Integrated Framework for Improving Large-Scale Hierarchical Classification. ICMLA 2017: 281-288 - [c61]Jeff Offutt, Paul Ammann, Kinga Dobolyi, Chris Kauffmann, Jaime Lester, Upsorn Praphamontripong, Huzefa Rangwala, Sanjeev Setia, Pearl Y. Wang, Liz White:
A Novel Self-Paced Model for Teaching Programming. L@S 2017: 177-180 - [c60]Yifeng Gao, Qingzhe Li, Xiaosheng Li, Jessica Lin, Huzefa Rangwala:
TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory. ECML/PKDD (3) 2017: 428-431 - [c59]Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan:
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. RecSys 2017: 23-31 - [i8]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-down Hierarchical Classification. CoRR abs/1706.01214 (2017) - [i7]Azad Naik, Huzefa Rangwala:
Embedding Feature Selection for Large-scale Hierarchical Classification. CoRR abs/1706.01581 (2017) - [i6]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning. CoRR abs/1706.01583 (2017) - [i5]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
Grade Prediction with Temporal Course-wise Influence. CoRR abs/1709.05433 (2017) - 2016
- [j20]Azad Naik, Huzefa Rangwala:
Large-scale hierarchical classification with rare categories and inconsistencies. AI Matters 2(3): 27-29 (2016) - [j19]Asmaa Elbadrawy, Agoritsa Polyzou, Zhiyun Ren, Mackenzie Sweeney, George Karypis, Huzefa Rangwala:
Predicting Student Performance Using Personalized Analytics. Computer 49(4): 61-69 (2016) - [j18]Nima Akhlaghi, Clayton A. Baker, Mohamed Lahlou, Hozaifah Zafar, Karthik G. Murthy, Huzefa Rangwala, Jana Kosecka, Wilsaan M. Joiner, Joseph J. Pancrazio, Siddhartha Sikdar:
Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles. IEEE Trans. Biomed. Eng. 63(8): 1687-1698 (2016) - [c58]Nathan LaPierre, Mohammad Arifur Rahman, Huzefa Rangwala:
CAMIL: Clustering and Assembly with Multiple Instance Learning for phenotype prediction. BIBM 2016: 33-40 - [c57]Azad Naik, Huzefa Rangwala:
Embedding feature selection for large-scale hierarchical classification. IEEE BigData 2016: 1212-1221 - [c56]Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan:
A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events. CIKM 2016: 509-518 - [c55]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-Down Hierarchical Classification. DSAA 2016: 379-388 - [c54]Mack Sweeney, Jaime Lester, Huzefa Rangwala, Aditya Johri:
Next-Term Student Performance Prediction: A Recommender Systems Approach. EDM 2016: 7 - [c53]Zhiyun Ren, Huzefa Rangwala, Aditya Johri:
Predicting Performance on MOOC Assessments using Multi-Regression Models. EDM 2016: 484-489 - [c52]Clayton A. Baker, Nima Akhlaghi, Huzefa Rangwala, Jana Kosecká, Siddhartha Sikdar:
Real-time, ultrasound-based control of a virtual hand by a trans-radial amputee. EMBC 2016: 3219-3222 - [c51]Yifeng Gao, Jessica Lin, Huzefa Rangwala:
Iterative Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. ICMLA 2016: 7-12 - [c50]Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. KDD 2016: 1095-1104 - [c49]Omaima Almatrafi, Huzefa Rangwala, Aditya Johri, Jaime Lester:
Using Learning Analytics to Trace Academic Trajectories of CS and IT Students to Better Understanding Successful Pathways to Graduation (Abstract Only). SIGCSE 2016: 691 - [i4]Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. CoRR abs/1602.08033 (2016) - [i3]Azad Naik, Huzefa Rangwala:
Filter based Taxonomy Modification for Improving Hierarchical Classification. CoRR abs/1603.00772 (2016) - [i2]Mack Sweeney, Huzefa Rangwala, Jaime Lester, Aditya Johri:
Next-Term Student Performance Prediction: A Recommender Systems Approach. CoRR abs/1604.01840 (2016) - [i1]Zhiyun Ren, Huzefa Rangwala, Aditya Johri:
Predicting Performance on MOOC Assessments using Multi-Regression Models. CoRR abs/1605.02269 (2016) - 2015
- [j17]Nuttachat Wisittipanit, Huzefa Rangwala, Masoumeh Sikaroodi, Ali Keshavarzian, Ece A. Mutlu, Patrick Gillevet:
Classification methods for the analysis of LH-PCR data associated with inflammatory bowel disease patients. Int. J. Bioinform. Res. Appl. 11(2): 111-129 (2015) - [j16]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang:
Predicting Protein Function Using Multiple Kernels. IEEE ACM Trans. Comput. Biol. Bioinform. 12(1): 219-233 (2015) - [c48]Mack Sweeney, Jaime Lester, Huzefa Rangwala:
Next-term student grade prediction. IEEE BigData 2015: 970-975 - [c47]Azad Naik, Huzefa Rangwala:
A ranking-based approach for hierarchical classification. DSAA 2015: 1-10 - [c46]Nathan LaPierre, Huzefa Rangwala:
Predicting Clinical Phenotype Using OTU-Based Metagenome Representation. ICDM Workshops 2015: 156-163 - [c45]Jean Michel Rouly, Huzefa Rangwala, Aditya Johri:
What Are We Teaching?: Automated Evaluation of CS Curricula Content Using Topic Modeling. ICER 2015: 189-197 - [c44]Xing Wang, Yifeng Gao, Jessica Lin, Huzefa Rangwala, Ranjeev Mittu:
A Machine Learning Approach to False Alarm Detection for Critical Arrhythmia Alarms. ICMLA 2015: 202-207 - [c43]Anvardh Nanduri, Huzefa Rangwala:
Predicting New Friendships in Social Networks. ICMLA 2015: 521-526 - [c42]Nikhil Muralidhar, Huzefa Rangwala, Eui-Hong Sam Han:
Recommending Temporally Relevant News Content from Implicit Feedback Data. ICTAI 2015: 689-696 - [c41]Anveshi Charuvaka, Huzefa Rangwala:
HierCost: Improving Large Scale Hierarchical Classification with Cost Sensitive Learning. ECML/PKDD (1) 2015: 675-690 - [c40]Anveshi Charuvaka, Huzefa Rangwala:
Approximate block coordinate descent for large scale hierarchical classification. SAC 2015: 837-844 - [c39]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Predicting Preference Tags to Improve Item Recommendation. SDM 2015: 864-872 - 2014
- [j15]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Erratum to "Protein Function Prediction Using Multilabel Ensemble Classification". IEEE ACM Trans. Comput. Biol. Bioinform. 11(1): 265 (2014) - [j14]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Protein Function Prediction withIncomplete Annotations. IEEE ACM Trans. Comput. Biol. Bioinform. 11(3): 579-591 (2014) - [j13]Gaurav Pandey, Huzefa Rangwala:
Guest Editorial for Special Section on BIOKDD2013. IEEE ACM Trans. Comput. Biol. Bioinform. 11(5): 773-774 (2014) - [j12]Anveshi Charuvaka, Huzefa Rangwala:
Classifying Protein Sequences Using Regularized Multi-Task Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 11(6): 1087-1098 (2014) - [c38]Anveshi Charuvaka, Huzefa Rangwala:
Convex multi-task relationship learning using hinge loss. CIDM 2014: 63-70 - [c37]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
FLIP: Active Learning for Relational Network Classification. ECML/PKDD (3) 2014: 1-18 - [c36]Huzefa Rangwala, Anveshi Charuvaka, Zeehasham Rasheed:
Machine Learning Approaches for Metagenomics. ECML/PKDD (3) 2014: 512-515 - 2013
- [j11]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
16S rRNA metagenome clustering and diversity estimation using locality sensitive hashing. BMC Syst. Biol. 7(S-4): S11 (2013) - [j10]Sharath Hiremagalore, Chen Liang, Angelos Stavrou, Huzefa Rangwala:
Improving network response times using social information. Soc. Netw. Anal. Min. 3(2): 209-220 (2013) - [j9]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Protein Function Prediction Using Multilabel Ensemble Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 10(4): 1045-1057 (2013) - [c35]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets Using Multi-task Learning. ICTAI 2013: 390-397 - [c34]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang:
Protein Function Prediction by Integrating Multiple Kernels. IJCAI 2013: 1869-1875 - [c33]Zeehasham Rasheed, Huzefa Rangwala:
A Map-Reduce Framework for Clustering Metagenomes. IPDPS Workshops 2013: 549-558 - [c32]Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
Relevant Subsequence Detection with Sparse Dictionary Learning. ECML/PKDD (1) 2013: 401-416 - [c31]Guo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang:
Protein Function Prediction Using Dependence Maximization. ECML/PKDD (1) 2013: 574-589 - [c30]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Sparsification and Sampling of Networks for Collective Classification. SBP 2013: 293-302 - [c29]Samuel J. Blasiak, Huzefa Rangwala, Sithu Sudarsan:
Joint Segmentation and Clustering in Text Corpuses. SDM 2013: 485-493 - [c28]Huzefa Rangwala, Zeehasham Rasheed:
MC-MinH: Metagenome Clustering using Minwise based Hashing. SDM 2013: 677-685 - [e1]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] - 2012
- [j8]Zeehasham Rasheed, Huzefa Rangwala:
Metagenomic Taxonomic Classification Using Extreme Learning Machines. J. Bioinform. Comput. Biol. 10(5) (2012) - [c27]Guo-Xian Yu, Guoji Zhang, Huzefa Rangwala, Carlotta Domeniconi, Zhiwen Yu:
Protein function prediction using weak-label learning. BCB 2012: 202-209 - [c26]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
LSH-Div: Species diversity estimation using locality sensitive hashing. BIBM 2012: 1-6 - [c25]Zeehasham Rasheed, Huzefa Rangwala, Patrick Gillevet:
Classification and clustering in metagenomics with unified data management and computational framework. BIBM Workshops 2012: 965-967 - [c24]Anveshi Charuvaka, Huzefa Rangwala:
Multi-task Learning for Classifying Proteins Using Dual Hierarchies. ICDM 2012: 834-839 - [c23]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Multi-label Collective Classification Using Adaptive Neighborhoods. ICMLA (1) 2012: 427-432 - [c22]Guo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu:
Transductive multi-label ensemble classification for protein function prediction. KDD 2012: 1077-1085 - [c21]Chaitanya Yavvari, Arnur G. Tokhtabayev, Huzefa Rangwala, Angelos Stavrou:
Malware Characterization Using Behavioral Components. MMM-ACNS 2012: 226-239 - [c20]Pu Wang, Carlotta Domeniconi, Huzefa Rangwala, Kathryn B. Laskey:
Feature Enriched Nonparametric Bayesian Co-clustering. PAKDD (1) 2012: 517-529 - [c19]Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
A Family of Feed-Forward Models for Protein Sequence Classification. ECML/PKDD (2) 2012: 419-434 - [c18]Samuel J. Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
Beam Methods for the Profile Hidden Markov Model. SDM 2012: 331-342 - [c17]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
Efficient Clustering of Metagenomic Sequences using Locality Sensitive Hashing. SDM 2012: 1023-1034 - 2011
- [c16]Chen Liang, Sharath Hiremagalore, Angelos Stavrou, Huzefa Rangwala:
Predicting Network Response Times Using Social Information. ASONAM 2011: 527-531 - [c15]Zeehasham Rasheed, Huzefa Rangwala:
TAC-ELM: Metagenomic Taxonomic Classification with Extreme Learning Machines. BICoB 2011: 92-97 - [c14]Sheng Li, Huzefa Rangwala:
An Information Theoretic Approach for the Analysis of RNA and DNA Binding Sites. BICoB 2011: 184-189 - [c13]Nuttachat Wisittipanit, Huzefa Rangwala, Masoumeh Sikaroodi, Ali Keshavarzian, Ece A. Mutlu, Patrick Gillevet:
Profiling Microbial Communities using SSU rRNA Sequence and LH-PCR Data. BICoB 2011: 190-195 - [c12]Syed Faraz Mahmood, Huzefa Rangwala:
GPU-Euler: Sequence Assembly Using GPGPU. HPCC 2011: 153-160 - [c11]Nuttachat Wisittipanit, Huzefa Rangwala, Patrick Gillevet:
Analysis of Microbiome Data across Inflammatory Bowel Disease Patients. ICMLA (2) 2011: 200-205 - [c10]Sam Blasiak, Huzefa Rangwala:
A Hidden Markov Model Variant for Sequence Classification. IJCAI 2011: 1192-1197 - [c9]Tanwistha Saha, Carlotta Domeniconi, Huzefa Rangwala:
Detection of Communities and Bridges in Weighted Networks. MLDM 2011: 584-598 - 2010
- [j7]Huzefa Rangwala, Salman Jamali:
Defining a Coparticipation Network Using Comments on Digg. IEEE Intell. Syst. 25(4): 36-45 (2010) - [j6]Rezwan Ahmed, Huzefa Rangwala, George Karypis:
Toptmh: Topology Predictor for transmembrane alpha-helices. J. Bioinform. Comput. Biol. 8(1): 39-57 (2010) - [c8]Anveshi Charuvaka, Huzefa Rangwala:
Evaluation of short read metagenomic assembly. BIBM 2010: 171-178 - [c7]Huzefa Rangwala:
Multiple Kernel Learning for Fold Recognition. BICoB 2010: 7-12 - [c6]Huzefa Rangwala, Salman Jamali:
Co-Participation Networks Using Comment Information. ICWSM 2010
2000 – 2009
- 2009
- [j5]Huzefa Rangwala, Christopher Kauffman, George Karypis:
svmPRAT: SVM-based Protein Residue Annotation Toolkit. BMC Bioinform. 10: 439 (2009) - [j4]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) - [c5]Huzefa Rangwala, Christopher Kauffman, George Karypis:
A Kernel Framework for Protein Residue Annotation. PAKDD 2009: 439-451 - 2008
- [c4]Huzefa Rangwala, George Karypis:
fRMSDAlign: Protein Sequence Alignment Using Predicted Local Structure Information for Pairs with Low Sequence Identity. APBC 2008: 111-122 - [c3]Ruinan Zhang, Huzefa Rangwala, George Karypis:
Genome Alignments Using MPI-LAGAN. BIBM 2008: 437-440 - [c2]Rezwan Ahmed, Huzefa Rangwala, George Karypis:
TOPTMH: Topology Predictor for Transmembrane alpha-Helices. ECML/PKDD (1) 2008: 23-38 - 2007
- [j3]Huzefa Rangwala, George Karypis:
Incremental window-based protein sequence alignment algorithms. Bioinform. 23(2): 17-23 (2007) - 2006
- [j2]Huzefa Rangwala, George Karypis:
Building multiclass classifiers for remote homology detection and fold recognition. BMC Bioinform. 7: 455 (2006) - 2005
- [j1]Huzefa Rangwala, George Karypis:
Profile-based direct kernels for remote homology detection and fold recognition. Bioinform. 21(23): 4239-4247 (2005) - [c1]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
Coauthor Index
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