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2020 – today
- 2024
[j13]Deming Chu
, Fan Zhang, Wenjie Zhang, Xuemin Lin, Ying Zhang, Yinglong Xia, Chenyi Zhang:
Discovering and Maintaining the Best $k$k in Core Decomposition. IEEE Trans. Knowl. Data Eng. 36(11): 5954-5971 (2024)- [c81]Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong:
Hierarchical Multi-Marginal Optimal Transport for Network Alignment. AAAI 2024: 16660-16668 - [c80]Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong:
Deceptive Fairness Attacks on Graphs via Meta Learning. ICLR 2024 - [c79]Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo:
Mixture of Weak and Strong Experts on Graphs. ICLR 2024 - [c78]Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna:
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. IPDPS 2024: 926-937 - [c77]Hanjia Lyu, Song Jiang, Hanqing Zeng, Yinglong Xia, Qifan Wang, Si Zhang, Ren Chen, Christopher Leung, Jiajie Tang, Jiebo Luo:
LLM-Rec: Personalized Recommendation via Prompting Large Language Models. NAACL-HLT (Findings) 2024: 583-612 - [c76]Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz:
RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. NAACL-HLT 2024: 5784-5809 - [i19]Gangda Deng, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor K. Prasanna:
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. CoRR abs/2402.05396 (2024) - [i18]Hanjia Lyu, Hanqing Zeng, Yinglong Xia, Ren Chen, Jiebo Luo:
Retrieval Augmentation via User Interest Clustering. CoRR abs/2408.03886 (2024) - 2023
- [c75]Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang:
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. ECAI 2023: 2307-2314 - [c74]Zhichen Zeng, Ruike Zhu, Yinglong Xia, Hanqing Zeng, Hanghang Tong:
Generative Graph Dictionary Learning. ICML 2023: 40749-40769 - [c73]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). KDD 2023: 5891-5892 - [c72]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c71]Gangda Deng, Ömer Faruk Akgül, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Jianbo Li, Viktor K. Prasanna:
An Efficient Distributed Graph Engine for Deep Learning on Graphs. SC Workshops 2023: 922-931 - [c70]Si Zhang, Yinglong Xia, Yan Zhu, Hanghang Tong:
Representation Learning on Dynamic Network of Networks. SDM 2023: 298-306 - [c69]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi:
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM 2023: 442-450 - [c68]Zhichen Zeng, Si Zhang, Yinglong Xia, Hanghang Tong:
PARROT: Position-Aware Regularized Optimal Transport for Network Alignment. WWW 2023: 372-382 - [i17]Hanjia Lyu, Song Jiang, Hanqing Zeng, Yinglong Xia, Jiebo Luo:
LLM-Rec: Personalized Recommendation via Prompting Large Language Models. CoRR abs/2307.15780 (2023) - [i16]Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang:
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. CoRR abs/2308.00894 (2023) - [i15]Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong:
Hierarchical Multi-Marginal Optimal Transport for Network Alignment. CoRR abs/2310.04470 (2023) - [i14]Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz:
Resprompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. CoRR abs/2310.04743 (2023) - [i13]Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong:
Deceptive Fairness Attacks on Graphs via Meta Learning. CoRR abs/2310.15653 (2023) - [i12]Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo:
Mixture of Weak & Strong Experts on Graphs. CoRR abs/2311.05185 (2023) - 2022
- [c67]Yuheng Zhang, Hanghang Tong, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying:
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning. AAAI 2022: 9118-9126 - [c66]Yian Wang, Jian Kang, Yinglong Xia, Jiebo Luo, Hanghang Tong:
iFiG: Individually Fair Multi-view Graph Clustering. IEEE Big Data 2022: 329-338 - [c65]Yuheng Zhang, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying, Hanghang Tong:
Active Heterogeneous Graph Neural Networks with Per-step Meta-Q-Learning. ICDM 2022: 1329-1334 - [c64]Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong:
Joint Knowledge Graph Completion and Question Answering. KDD 2022: 1098-1108 - [c63]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). KDD 2022: 4906-4907 - [c62]Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang:
Explainable Fairness in Recommendation. SIGIR 2022: 681-691 - [c61]Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong:
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network. WWW 2022: 1214-1225 - [i11]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. CoRR abs/2201.07858 (2022) - [i10]Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong:
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network. CoRR abs/2202.13547 (2022) - [i9]Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang:
Explainable Fairness in Recommendation. CoRR abs/2204.11159 (2022) - 2021
- [j12]Chen Chen, Yinglong Xia, Hui Zang, Jundong Li, Huan Liu, Hanghang Tong:
Incremental one-class collaborative filtering with co-evolving side networks. Knowl. Inf. Syst. 63(1): 105-124 (2021) - [j11]Meijia Wang, Jian Kang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong:
Graph Ranking Auditing: Problem Definition and Fast Solutions. IEEE Trans. Knowl. Data Eng. 33(10): 3366-3380 (2021) - [c60]Zhe Xu, Si Zhang, Yinglong Xia, Liang Xiong, Jiejun Xu, Hanghang Tong:
DESTINE: Dense Subgraph Detection on Multi-Layered Networks. CIKM 2021: 3558-3562 - [c59]Si Zhang, Hanghang Tong, Long Jin, Yinglong Xia, Yunsong Guo:
Balancing Consistency and Disparity in Network Alignment. KDD 2021: 2212-2222 - [c58]Lingfei Wu, Jiliang Tang, Yinglong Xia, Jian Pei, Xiaojie Guo:
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). KDD 2021: 4167-4168 - [c57]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. NeurIPS 2021: 9061-9073 - [c56]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS 2021: 19665-19679 - [i8]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen:
Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR abs/2111.10447 (2021) - 2020
- [c55]Zhe Xu, Si Zhang, Yinglong Xia, Liang Xiong, Hanghang Tong:
Ranking on Network of Heterogeneous Information Networks. IEEE BigData 2020: 848-857 - [c54]Deming Chu, Fan Zhang, Xuemin Lin, Wenjie Zhang, Ying Zhang, Yinglong Xia, Chenyi Zhang:
Finding the Best k in Core Decomposition: A Time and Space Optimal Solution. ICDE 2020: 685-696 - [c53]Si Zhang, Hanghang Tong, Yinglong Xia, Liang Xiong, Jiejun Xu:
NetTrans: Neural Cross-Network Transformation. KDD 2020: 986-996 - [i7]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Revisiting Graph Neural Networks for Link Prediction. CoRR abs/2010.16103 (2020) - [i6]Alexandru Iosup, Ahmed Musaafir, Alexandru Uta, Arnau Prat-Pérez, Gábor Szárnyas, Hassan Chafi, Ilie Gabriel Tanase, Lifeng Nai, Michael J. Anderson, Mihai Capota, Narayanan Sundaram, Peter A. Boncz, Siegfried Depner, Stijn Heldens, Thomas Manhardt, Tim Hegeman, Wing Lung Ngai, Yinglong Xia:
The LDBC Graphalytics Benchmark. CoRR abs/2011.15028 (2020)
2010 – 2019
- 2019
- [j10]Ladjel Bellatreche, Carson Kai-Sang Leung, Yinglong Xia, Didier El Baz:
Advances in cloud and big data computing. Concurr. Comput. Pract. Exp. 31(2) (2019) - [j9]Qiang-Sheng Hua, Xuanhua Shi, Yinglong Xia, Howie Huang:
Guest Editorial: Special Issue on Algorithms and Systems on Big Graph Processing. Int. J. Parallel Program. 47(4): 641-643 (2019) - [c52]Rui Zhang, Hanghang Tong, Yinglong Xia, Yada Zhu:
Robust Embedded Deep K-means Clustering. CIKM 2019: 1181-1190 - [c51]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. KDD 2019: 1418-1428 - [c50]Yinglong Xia:
Roll of Unified Graph Analysis Platforms. KDD 2019: 3179 - [c49]Tianran Hu, Yinglong Xia, Jiebo Luo:
To Return or to Explore: Modelling Human Mobility and Dynamics in Cyberspace. WWW 2019: 705-716 - [i5]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. CoRR abs/1911.11119 (2019) - 2018
- [c48]Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong:
AURORA: Auditing PageRank on Large Graphs. IEEE BigData 2018: 713-722 - [c47]Scott Freitas, Nan Cao, Yinglong Xia, Duen Horng (Polo) Chau, Hanghang Tong:
Local Partition in Rich Graphs. IEEE BigData 2018: 1001-1008 - [c46]Jian Kang, Scott Freitas, Haichao Yu, Yinglong Xia, Nan Cao, Hanghang Tong:
X-Rank: Explainable Ranking in Complex Multi-Layered Networks. CIKM 2018: 1959-1962 - [c45]Li Zhou, Ren Chen, Yinglong Xia, Radu Teodorescu:
C-Graph: A Highly Efficient Concurrent Graph Reachability Query Framework. ICPP 2018: 79:1-79:10 - [c44]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. KDD 2018: 2506-2515 - [i4]Jian Kang, Hanghang Tong, Yinglong Xia, Wei Fan:
AURORA: Auditing PageRank on Large Graphs. CoRR abs/1803.05068 (2018) - [i3]Scott Freitas, Hanghang Tong, Nan Cao, Yinglong Xia:
Local Partition in Rich Graphs. CoRR abs/1803.05084 (2018) - [i2]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. CoRR abs/1805.11048 (2018) - 2017
- [j8]Lifeng Nai, Yinglong Xia, Ilie Gabriel Tanase, Hyesoon Kim:
Exploring big graph computing - An empirical study from architectural perspective. J. Parallel Distributed Comput. 108: 122-137 (2017) - [c43]Scott Freitas, Hanghang Tong, Nan Cao, Yinglong Xia:
Rapid Analysis of Network Connectivity. CIKM 2017: 2463-2466 - [c42]Qingsong Wen, Ren Chen, Lifeng Nai, Li Zhou, Yinglong Xia:
Finding Top K Shortest Simple Paths with Improved Space Efficiency. GRADES@SIGMOD/PODS 2017: 13:1-13:6 - [e2]Srinivas Alum, Ananth Kalyanaraman, Bora Uçar, Kishore Kothapalli, Mahantesh Halappanavar, Kamesh Madduri, Madhu Govindaraju, Yinglong Xia, Sushil K. Prasad, Martina Barnas, Ashish Sureka, Pankesh Patel, Vikas Saxena, Sanjay Goel:
Tenth International Conference on Contemporary Computing, IC3 2017, Noida, India, August 10-12, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3077-8 [contents] - 2016
- [j7]Anni Coden, W. Sabrina Lin, Keith Houck, Michael A. Tanenblatt, Jeff Boston, Julie MacNaught, Danny Soroker, Justin D. Weisz, Shimei Pan, Jui-Hsin Lai, Jie Lu, Steve Wood, Yinglong Xia, Ching-Yung Lin:
Uncovering insider threats from the digital footprints of individuals. IBM J. Res. Dev. 60(4): 8 (2016) - [j6]Alexandru Iosup, Tim Hegeman, Wing Lung Ngai, Stijn Heldens, Arnau Prat-Pérez, Thomas Manhardt, Hassan Chafi, Mihai Capota, Narayanan Sundaram, Michael J. Anderson, Ilie Gabriel Tanase, Yinglong Xia, Lifeng Nai, Peter A. Boncz:
LDBC Graphalytics: A Benchmark for Large-Scale Graph Analysis on Parallel and Distributed Platforms. Proc. VLDB Endow. 9(13): 1317-1328 (2016) - [c41]James Schaffer, Brandon Huynh, John O'Donovan, Tobias Höllerer, Yinglong Xia, W. Sabrina Lin:
An analysis of student behavior in two massive open online courses. ASONAM 2016: 380-385 - [c40]Li Zhou, Yinglong Xia, Hui Zang, Jian Xu, Mingzhen Xia:
An edge-set based large scale graph processing system. IEEE BigData 2016: 1664-1669 - [c39]Charalampos Chelmis, Sutanay Choudhury, Arindam Pal, Anand V. Panangadan, Weiqin Tong, Yinglong Xia:
ParLearning Introduction and Committees. IPDPS Workshops 2016: 1390-1391 - [e1]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
- [c38]Guojing Cong, Ilie Gabriel Tanase, Yinglong Xia:
Accelerating Minimum Spanning Forest Computations on Multicore Platforms. Euro-Par Workshops 2015: 541-552 - [c37]Jianting Zhang, Simin You, Yinglong Xia:
Prototyping A Web-based High-Performance Visual Analytics Platform for Origin-Destination Data: A Case study of NYC Taxi Trip Records. UrbanGIS@SIGSPATIAL 2015: 16-23 - [c36]Chun-Hsi Huang, Gwo Giun Chris Lee, Chun-Fu (Richard) Chen, Yinglong Xia, Ching-Yung Lin:
Reconfigurable filter bank design via principal component analysis and low rank approximation. GlobalSIP 2015: 473-477 - [c35]Ching-Yung Lin, Danny L. Yeh, Nan Cao, Jui-Hsin Lai, Chun-Fu (Richard) Chen, Conglei Shi, Jie Lu, Jason Crawford, Keith Houck, Yinglong Xia, Wan-Yi Sabrina Lin, Richard B. Hull, Fenno F. Terry Heath III, Piyawadee Sukaviriya, SweeFen Goh:
IBM system G Social Media Solution: Analyze multimedia content, people, and network dynamics in context. ICME Workshops 2015: 1-4 - [c34]Yinglong Xia, Lifeng Nai, Jui-Hsin Lai:
Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals. IPDPS 2015: 936-945 - [c33]Sutanay Choudhury, Arindam Pal, Anand V. Panangadan, Yinglong Xia:
ParLearning Introduction and Committees. IPDPS Workshops 2015: 1152-1153 - [c32]Chun-Fu (Richard) Chen, Gwo Giun Chris Lee, Yinglong Xia, W. Sabrina Lin, Toyotaro Suzumura, Ching-Yung Lin:
Efficient Multi-training Framework of Image Deep Learning on GPU Cluster. ISM 2015: 489-494 - [c31]Lifeng Nai, Yinglong Xia, Ilie Gabriel Tanase, Hyesoon Kim, Ching-Yung Lin:
GraphBIG: understanding graph computing in the context of industrial solutions. SC 2015: 69:1-69:12 - [c30]Dakshi Agrawal, Ali Raza Butt, Kshitij A. Doshi, Josep Lluís Larriba-Pey, Min Li, Frederick R. Reiss, Francois Raab, Berni Schiefer, Toyotaro Suzumura, Yinglong Xia:
SparkBench - A Spark Performance Testing Suite. TPCTC 2015: 26-44 - 2014
- [j5]Nam Ma, Yinglong Xia, Viktor K. Prasanna:
Data Parallel Implementation of Belief Propagation in Factor Graphs on Multi-core Platforms. Int. J. Parallel Program. 42(1): 219-237 (2014) - [c29]Yinglong Xia, Ilie Gabriel Tanase, Lifeng Nai, Wei Tan, Yanbin Liu, Jason Crawford, Ching-Yung Lin:
Graph analytics and storage. IEEE BigData 2014: 942-951 - [c28]Lifeng Nai, Yinglong Xia, Ching-Yung Lin, Bo Hong, Hsien-Hsin S. Lee:
Cache-conscious graph collaborative filtering on multi-socket multicore systems. Conf. Computing Frontiers 2014: 32:1-32:10 - [c27]Yinglong Xia, Jui-Hsin Lai, Lifeng Nai, Ching-Yung Lin:
Concurrent image query using local random walk with restart on large scale graphs. ICME Workshops 2014: 1-6 - [c26]Abhinav Vishnu, Yinglong Xia:
ParLearning Introduction and Committees. IPDPS Workshops 2014: 1599-1600 - [c25]Hsuan-Yi Chu, Yinglong Xia, Anand V. Panangadan, Viktor K. Prasanna:
Wait-Free Primitives for Initializing Bayesian Network Structure Learning on Multicore Processors. IPDPS Workshops 2014: 1602-1611 - [c24]Ilie Gabriel Tanase, Yinglong Xia, Lifeng Nai, Yanbin Liu, Wei Tan, Jason Crawford, Ching-Yung Lin:
A Highly Efficient Runtime and Graph Library for Large-Scale Graph Analytics. GRADES 2014: 10:1-10:6 - 2013
- [c23]Peter Strazdins, Neal Naixue Xiong, Thomas Rauber, Yinglong Xia, Laurence T. Yang, Gudula Rünger:
PDSEC Introduction. IPDPS Workshops 2013: 1324-1325 - [c22]Sutanay Choudhury, George Chin Jr., Yinglong Xia:
ParLearning Introduction. IPDPS Workshops 2013: 1856-1858 - 2012
- [j4]Yinglong Xia, Viktor K. Prasanna:
Distributed Evidence Propagation in Junction Trees on Clusters. IEEE Trans. Parallel Distributed Syst. 23(7): 1169-1177 (2012) - [c21]Sutanay Choudhury, George Chin Jr., Yinglong Xia:
ParLearning Introduction. IPDPS Workshops 2012: 1905-1906 - [c20]Nam Ma, Yinglong Xia, Viktor K. Prasanna:
Task Parallel Implementation of Belief Propagation in Factor Graphs. IPDPS Workshops 2012: 1944-1953 - [c19]Nam Ma, Yinglong Xia, Viktor K. Prasanna:
Parallel Exact Inference on Multicore Using MapReduce. SBAC-PAD 2012: 187-194 - [c18]Jun Wang, Yinglong Xia:
Fast Graph Construction Using Auction Algorithm. UAI 2012: 873-882 - [i1]Jun Wang, Yinglong Xia:
Fast Graph Construction Using Auction Algorithm. CoRR abs/1210.4917 (2012) - 2011
- [j3]Yinglong Xia, Viktor K. Prasanna:
Parallel evidence propagation on multicore processors. J. Supercomput. 57(2): 189-202 (2011) - [c17]Nam Ma, Yinglong Xia, Viktor K. Prasanna:
Exploring Weak Dependencies in DAG Scheduling. IPDPS Workshops 2011: 591-598 - [c16]Yinglong Xia, Viktor K. Prasanna:
Self-Adaptive Evidence Propagation on Manycore Processors. IPDPS Workshops 2011: 1407-1416 - [c15]Nam Ma, Yinglong Xia, Viktor K. Prasanna:
Data Parallelism for Belief Propagation in Factor Graphs. SBAC-PAD 2011: 56-63 - 2010
- [j2]Yinglong Xia, Viktor K. Prasanna:
Parallel exact inference on the Cell Broadband Engine processor. J. Parallel Distributed Comput. 70(5): 558-572 (2010) - [j1]Yinglong Xia, Viktor K. Prasanna:
Scalable Node-Level Computation Kernels for Parallel Exact Inference. IEEE Trans. Computers 59(1): 103-115 (2010) - [c14]Yinglong Xia, Viktor K. Prasanna:
Collaborative scheduling of DAG structured computations on multicore processors. Conf. Computing Frontiers 2010: 63-72 - [c13]Qingbo Wang, Weirong Jiang, Yinglong Xia, Viktor K. Prasanna:
A message-passing multi-softcore architecture on FPGA for Breadth-first Search. FPT 2010: 70-77 - [c12]Hyeran Jeon, Yinglong Xia, Viktor K. Prasanna:
Parallel Exact Inference on a CPU-GPGPU Heterogenous System. ICPP 2010: 61-70 - [c11]Yinglong Xia, Viktor K. Prasanna, James Li:
Hierarchical Scheduling of DAG Structured Computations on Manycore Processors with Dynamic Thread Grouping. JSSPP 2010: 154-174 - [c10]Yinglong Xia, Viktor K. Prasanna:
Distributed Evidence Propagation in Junction Trees. SBAC-PAD 2010: 143-150
2000 – 2009
- 2009
- [c9]Yinglong Xia, Xiaojun Feng, Viktor K. Prasanna:
Parallel Evidence Propagation on Multicore Processors. PaCT 2009: 377-391 - 2008
- [c8]Yinglong Xia, Viktor K. Prasanna:
Junction tree decomposition for parallel exact inference. IPDPS 2008: 1-12 - [c7]Yinglong Xia, Viktor K. Prasanna:
Parallel exact inference on the cell broadband engine processor. SC 2008: 58 - 2007
- [c6]Yinglong Xia, Viktor K. Prasanna:
Parallel Exact Inference. PARCO 2007: 185-192 - [c5]Yinglong Xia, Viktor K. Prasanna:
Node Level Primitives for Parallel Exact Inference. SBAC-PAD 2007: 221-228 - 2005
- [c4]Yinglong Xia, Changshui Zhang, Shifeng Weng, Rongbin Liu:
Fault-Tolerant EM Algorithm for GMM in Sensor Networks. DMIN 2005: 166-172 - [c3]Yalin Zheng, Changshui Zhang, Yinglong Xia:
Type II Topological Logic C1T and Approximate Reasoning. FSKD (1) 2005: 243-252 - [c2]Yinglong Xia, Shifeng Weng, Changshui Zhang, Shao Li:
Mixture Random Effect Model Based Meta-analysis for Medical Data Mining. MLDM 2005: 630-640 - [c1]Rongbin Liu, Changshui Zhang, Yinglong Xia:
Importance Feature Sampling in Random Subspace. VISION 2005: 192-197
Coauthor Index
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