Fault-Tolerant EM Algorithm for GMM in Sensor Networks. - Yinglong Xia; Changshui Zhang; Shifeng Weng; Rongbin Liu (DMIN, 2005)

Type II Topological Logic C1T and Approximate Reasoning. - Yalin Zheng; Changshui Zhang; Yinglong Xia (FSKD (1), 2005)

Mixture Random Effect Model Based Meta-analysis for Medical Data Mining. - Yinglong Xia; Shifeng Weng; Changshui Zhang; Shao Li (MLDM, 2005)

Importance Feature Sampling in Random Subspace. - Rongbin Liu; Changshui Zhang; Yinglong Xia (VISION, 2005)

Parallel Exact Inference. - Yinglong Xia; Viktor K. Prasanna (PARCO, 2007)

Node Level Primitives for Parallel Exact Inference. - Yinglong Xia; Viktor K. Prasanna (SBAC-PAD, 2007)

Junction tree decomposition for parallel exact inference. - Yinglong Xia; Viktor K. Prasanna (IPDPS, 2008)

Parallel Evidence Propagation on Multicore Processors. - Yinglong Xia; Xiaojun Feng; Viktor K. Prasanna (PaCT, 2009)

Collaborative scheduling of DAG structured computations on multicore processors. - Yinglong Xia; Viktor K. Prasanna (Conf. Computing Frontiers, 2010)

A message-passing multi-softcore architecture on FPGA for Breadth-first Search. - Qingbo Wang; Weirong Jiang; Yinglong Xia; Viktor K. Prasanna (FPT, 2010)

Parallel Exact Inference on a CPU-GPGPU Heterogenous System. - Hyeran Jeon; Yinglong Xia; Viktor K. Prasanna (ICPP, 2010)

Hierarchical Scheduling of DAG Structured Computations on Manycore Processors with Dynamic Thread Grouping. - Yinglong Xia; Viktor K. Prasanna; James Li (JSSPP, 2010)

Distributed Evidence Propagation in Junction Trees. - Yinglong Xia; Viktor K. Prasanna (SBAC-PAD, 2010)

Parallel exact inference on the Cell Broadband Engine processor. - Yinglong Xia; Viktor K. Prasanna (J. Parallel Distributed Comput., 2010)

Scalable Node-Level Computation Kernels for Parallel Exact Inference. - Yinglong Xia; Viktor K. Prasanna (IEEE Trans. Computers, 2010)

Exploring Weak Dependencies in DAG Scheduling. - Nam Ma; Yinglong Xia; Viktor K. Prasanna (IPDPS Workshops, 2011)

Self-Adaptive Evidence Propagation on Manycore Processors. - Yinglong Xia; Viktor K. Prasanna (IPDPS Workshops, 2011)

Data Parallelism for Belief Propagation in Factor Graphs. - Nam Ma; Yinglong Xia; Viktor K. Prasanna (SBAC-PAD, 2011)

Parallel evidence propagation on multicore processors. - Yinglong Xia; Viktor K. Prasanna (J. Supercomput., 2011)

Task Parallel Implementation of Belief Propagation in Factor Graphs. - Nam Ma; Yinglong Xia; Viktor K. Prasanna (IPDPS Workshops, 2012)

Parallel Exact Inference on Multicore Using MapReduce. - Nam Ma; Yinglong Xia; Viktor K. Prasanna (SBAC-PAD, 2012)

Fast Graph Construction Using Auction Algorithm. - Jun Wang; Yinglong Xia (UAI, 2012)

Distributed Evidence Propagation in Junction Trees on Clusters. - Yinglong Xia; Viktor K. Prasanna (IEEE Trans. Parallel Distributed Syst., 2012)

ParLearning Introduction. - Sutanay Choudhury; George Chin Jr.; Yinglong Xia (IPDPS Workshops, 2013)

PDSEC Introduction. - Peter Strazdins; Neal Naixue Xiong; Thomas Rauber; Yinglong Xia; Laurence T. Yang; Gudula Rünger (IPDPS Workshops, 2013)

Graph analytics and storage. - Yinglong Xia; Ilie Gabriel Tanase; Lifeng Nai; Wei Tan 001; Yanbin Liu; Jason Crawford; Ching-Yung Lin (IEEE BigData, 2014)

Cache-conscious graph collaborative filtering on multi-socket multicore systems. - Lifeng Nai; Yinglong Xia; Ching-Yung Lin; Bo Hong; Hsien-Hsin S. Lee (Conf. Computing Frontiers, 2014)

Concurrent image query using local random walk with restart on large scale graphs. - Yinglong Xia; Jui-Hsin Lai; Lifeng Nai; Ching-Yung Lin (ICME Workshops, 2014)

Wait-Free Primitives for Initializing Bayesian Network Structure Learning on Multicore Processors. - Hsuan-Yi Chu; Yinglong Xia; Anand V. Panangadan; Viktor K. Prasanna (IPDPS Workshops, 2014)

ParLearning Introduction and Committees. - Abhinav Vishnu; Yinglong Xia (IPDPS Workshops, 2014)

A Highly Efficient Runtime and Graph Library for Large-Scale Graph Analytics. - Ilie Gabriel Tanase; Yinglong Xia; Lifeng Nai; Yanbin Liu; Wei Tan 001; Jason Crawford; Ching-Yung Lin (GRADES, 2014)

Data Parallel Implementation of Belief Propagation in Factor Graphs on Multi-core Platforms. - Nam Ma; Yinglong Xia; Viktor K. Prasanna (Int. J. Parallel Program., 2014)

Accelerating Minimum Spanning Forest Computations on Multicore Platforms. - Guojing Cong; Ilie Gabriel Tanase; Yinglong Xia (Euro-Par Workshops, 2015)

Prototyping A Web-based High-Performance Visual Analytics Platform for Origin-Destination Data: A Case study of NYC Taxi Trip Records. - Jianting Zhang; Simin You; Yinglong Xia (UrbanGIS@SIGSPATIAL, 2015)

Reconfigurable filter bank design via principal component analysis and low rank approximation. - Chun-Hsi Huang; Gwo Giun Chris Lee; Chun-Fu (Richard) Chen; Yinglong Xia; Ching-Yung Lin (GlobalSIP, 2015)

IBM system G Social Media Solution: Analyze multimedia content, people, and network dynamics in context. - Ching-Yung Lin; Danny L. Yeh; Nan Cao 001; Jui-Hsin Lai; Chun-Fu (Richard) Chen; Conglei Shi; Jie Lu 002; Jason Crawford; Keith Houck; Yinglong Xia; Wan-Yi Sabrina Lin; Richard B. Hull; et al. (ICME Workshops, 2015)

ParLearning Introduction and Committees. - Sutanay Choudhury; Arindam Pal 001; Anand V. Panangadan; Yinglong Xia (IPDPS Workshops, 2015)

Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals. - Yinglong Xia; Lifeng Nai; Jui-Hsin Lai (IPDPS, 2015)

Efficient Multi-training Framework of Image Deep Learning on GPU Cluster. - Chun-Fu (Richard) Chen; Gwo Giun Chris Lee; Yinglong Xia; W. Sabrina Lin; Toyotaro Suzumura; Ching-Yung Lin (ISM, 2015)

GraphBIG: understanding graph computing in the context of industrial solutions. - Lifeng Nai; Yinglong Xia; Ilie Gabriel Tanase; Hyesoon Kim; Ching-Yung Lin (SC, 2015)

SparkBench - A Spark Performance Testing Suite. - 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 (TPCTC, 2015)

An analysis of student behavior in two massive open online courses. - James Schaffer; Brandon Huynh; John O'Donovan; Tobias Höllerer; Yinglong Xia; W. Sabrina Lin (ASONAM, 2016)

An edge-set based large scale graph processing system. - Li Zhou 012; Yinglong Xia; Hui Zang; Jian Xu; Mingzhen Xia (IEEE BigData, 2016)

ParLearning Introduction and Committees. - Charalampos Chelmis; Sutanay Choudhury; Arindam Pal 001; Anand V. Panangadan; Weiqin Tong; Yinglong Xia (IPDPS Workshops, 2016)

Uncovering insider threats from the digital footprints of individuals. - 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 002; Steve Wood; et al. (IBM J. Res. Dev., 2016)

LDBC Graphalytics: A Benchmark for Large-Scale Graph Analysis on Parallel and Distributed Platforms. - 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; et al. (Proc. VLDB Endow., 2016)

Rapid Analysis of Network Connectivity. - Scott Freitas; Hanghang Tong; Nan Cao 001; Yinglong Xia (CIKM, 2017)

Finding Top K Shortest Simple Paths with Improved Space Efficiency. - Qingsong Wen; Ren Chen; Lifeng Nai; Li Zhou 012; Yinglong Xia (GRADES@SIGMOD/PODS, 2017)

Exploring big graph computing - An empirical study from architectural perspective. - Lifeng Nai; Yinglong Xia; Ilie Gabriel Tanase; Hyesoon Kim (J. Parallel Distributed Comput., 2017)

Local Partition in Rich Graphs. - Scott Freitas; Nan Cao 001; Yinglong Xia; Duen Horng (Polo) Chau; Hanghang Tong (IEEE BigData, 2018)

AURORA: Auditing PageRank on Large Graphs. - Jian Kang 008; Meijia Wang; Nan Cao 001; Yinglong Xia; Wei Fan 001; Hanghang Tong (IEEE BigData, 2018)

X-Rank: Explainable Ranking in Complex Multi-Layered Networks. - Jian Kang 008; Scott Freitas; Haichao Yu; Yinglong Xia; Nan Cao 001; Hanghang Tong (CIKM, 2018)

C-Graph: A Highly Efficient Concurrent Graph Reachability Query Framework. - Li Zhou 012; Ren Chen; Yinglong Xia; Radu Teodorescu (ICPP, 2018)

Scalable Spectral Clustering Using Random Binning Features. - Lingfei Wu 001; Pin-Yu Chen; Ian En-Hsu Yen; Fangli Xu; Yinglong Xia; Charu C. Aggarwal (KDD, 2018)

AURORA: Auditing PageRank on Large Graphs. - Jian Kang 008; Hanghang Tong; Yinglong Xia; Wei Fan 001 (CoRR, 2018)

Local Partition in Rich Graphs. - Scott Freitas; Hanghang Tong; Nan Cao 001; Yinglong Xia (CoRR, 2018)

Robust Embedded Deep K-means Clustering. - Rui Zhang 017; Hanghang Tong; Yinglong Xia; Yada Zhu (CIKM, 2019)

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. - Lingfei Wu 001; Ian En-Hsu Yen; Zhen Zhang 007; Kun Xu 005; Liang Zhao 002; Xi Peng 005; Yinglong Xia; Charu C. Aggarwal (KDD, 2019)

Roll of Unified Graph Analysis Platforms. - Yinglong Xia (KDD, 2019)

To Return or to Explore: Modelling Human Mobility and Dynamics in Cyberspace. - Tianran Hu; Yinglong Xia; Jiebo Luo 001 (WWW, 2019)

Advances in cloud and big data computing. - Ladjel Bellatreche; Carson Kai-Sang Leung; Yinglong Xia; Didier El Baz (Concurr. Comput. Pract. Exp., 2019)

Guest Editorial: Special Issue on Algorithms and Systems on Big Graph Processing. - Qiang-Sheng Hua; Xuanhua Shi; Yinglong Xia; Howie Huang (Int. J. Parallel Program., 2019)

Ranking on Network of Heterogeneous Information Networks. - Zhe Xu 007; Si Zhang; Yinglong Xia; Liang Xiong; Hanghang Tong (IEEE BigData, 2020)

Finding the Best k in Core Decomposition: A Time and Space Optimal Solution. - Deming Chu; Fan Zhang 036; Xuemin Lin 001; Wenjie Zhang 001; Ying Zhang 001; Yinglong Xia; Chenyi Zhang 002 (ICDE, 2020)

NetTrans: Neural Cross-Network Transformation. - Si Zhang; Hanghang Tong; Yinglong Xia; Liang Xiong; Jiejun Xu (KDD, 2020)

Revisiting Graph Neural Networks for Link Prediction. - Muhan Zhang; Pan Li 005; Yinglong Xia; Kai Wang; Long Jin (CoRR, 2020)

The LDBC Graphalytics Benchmark. - 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; et al. (CoRR, 2020)

DESTINE: Dense Subgraph Detection on Multi-Layered Networks. - Zhe Xu 007; Si Zhang; Yinglong Xia; Liang Xiong; Jiejun Xu; Hanghang Tong (CIKM, 2021)

The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). - Lingfei Wu 001; Jiliang Tang; Yinglong Xia; Jian Pei 001; Xiaojie Guo 002 (KDD, 2021)

Balancing Consistency and Disparity in Network Alignment. - Si Zhang; Hanghang Tong; Long Jin; Yinglong Xia; Yunsong Guo (KDD, 2021)

Decoupling the Depth and Scope of Graph Neural Networks. - Hanqing Zeng; Muhan Zhang; Yinglong Xia; Ajitesh Srivastava; Andrey Malevich; Rajgopal Kannan; Viktor K. Prasanna; Long Jin; Ren Chen (NeurIPS, 2021)

Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. - Muhan Zhang; Pan Li 005; Yinglong Xia; Kai Wang; Long Jin (NeurIPS, 2021)

Dynamic Graph Representation Learning via Graph Transformer Networks. - Weilin Cong; Yanhong Wu; Yuandong Tian; Mengting Gu; Yinglong Xia; Mehrdad Mahdavi; Chun-cheng Jason Chen (CoRR, 2021)

Incremental one-class collaborative filtering with co-evolving side networks. - Chen Chen 022; Yinglong Xia; Hui Zang; Jundong Li; Huan Liu 001; Hanghang Tong (Knowl. Inf. Syst., 2021)

Graph Ranking Auditing: Problem Definition and Fast Solutions. - Meijia Wang; Jian Kang 008; Nan Cao 001; Yinglong Xia; Wei Fan 001; Hanghang Tong (IEEE Trans. Knowl. Data Eng., 2021)

Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning. - Yuheng Zhang; Hanghang Tong; Yinglong Xia; Yan Zhu; Yuejie Chi; Lei Ying 001 (AAAI, 2022)

iFiG: Individually Fair Multi-view Graph Clustering. - Yian Wang 002; Jian Kang 008; Yinglong Xia; Jiebo Luo 001; Hanghang Tong (IEEE Big Data, 2022)

Active Heterogeneous Graph Neural Networks with Per-step Meta-Q-Learning. - Yuheng Zhang; Yinglong Xia; Yan Zhu; Yuejie Chi; Lei Ying 001; Hanghang Tong (ICDM, 2022)

Joint Knowledge Graph Completion and Question Answering. - Lihui Liu; Boxin Du; Jiejun Xu; Yinglong Xia; Hanghang Tong (KDD, 2022)

Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). - Lingfei Wu 001; Jian Pei 001; Jiliang Tang; Yinglong Xia; Xiaojie Guo 002 (KDD, 2022)

Explainable Fairness in Recommendation. - Yingqiang Ge; Juntao Tan; Yan Zhu; Yinglong Xia; Jiebo Luo 001; Shuchang Liu 001; Zuohui Fu; Shijie Geng; Zelong Li; Yongfeng Zhang (SIGIR, 2022)

RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network. - Jian Kang 008; Yan Zhu; Yinglong Xia; Jiebo Luo 001; Hanghang Tong (WWW, 2022)

User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. - Juntao Tan; Yingqiang Ge; Yan Zhu; Yinglong Xia; Jiebo Luo 001; Jianchao Ji; Yongfeng Zhang (ECAI, 2023)

Generative Graph Dictionary Learning. - Zhichen Zeng 001; Ruike Zhu; Yinglong Xia; Hanqing Zeng; Hanghang Tong (ICML, 2023)

Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). - Lingfei Wu 001; Jian Pei 001; Jiliang Tang; Yinglong Xia; Xiaojie Guo 002 (KDD, 2023)

RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. - Chuxu Zhang; Dongkuan Xu; Mojan Javaheripi; Subhabrata Mukherjee; Lingfei Wu 001; Yinglong Xia; Jundong Li; Meng Jiang 001; Yanzhi Wang (KDD, 2023)

An Efficient Distributed Graph Engine for Deep Learning on Graphs. - Gangda Deng; Ömer Faruk Akgül; Hongkuan Zhou; Hanqing Zeng; Yinglong Xia; Jianbo Li; Viktor K. Prasanna (SC Workshops, 2023)

DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. - Weilin Cong; Yanhong Wu; Yuandong Tian; Mengting Gu; Yinglong Xia; Chun-cheng Jason Chen; Mehrdad Mahdavi (SDM, 2023)

Representation Learning on Dynamic Network of Networks. - Si Zhang; Yinglong Xia; Yan Zhu; Hanghang Tong (SDM, 2023)

PARROT: Position-Aware Regularized Optimal Transport for Network Alignment. - Zhichen Zeng 001; Si Zhang; Yinglong Xia; Hanghang Tong (WWW, 2023)

LLM-Rec: Personalized Recommendation via Prompting Large Language Models. - Hanjia Lyu; Song Jiang 002; Hanqing Zeng; Yinglong Xia; Jiebo Luo 001 (CoRR, 2023)

Mixture of Weak & Strong Experts on Graphs. - Hanqing Zeng; Hanjia Lyu; Diyi Hu; Yinglong Xia; Jiebo Luo 001 (CoRR, 2023)

Hierarchical Multi-Marginal Optimal Transport for Network Alignment. - Zhichen Zeng 001; Boxin Du; Si Zhang; Yinglong Xia; Zhining Liu 002; Hanghang Tong (AAAI, 2024)

Deceptive Fairness Attacks on Graphs via Meta Learning. - Jian Kang 008; Yinglong Xia; Ross Maciejewski; Jiebo Luo 001; Hanghang Tong (ICLR, 2024)

Mixture of Weak and Strong Experts on Graphs. - Hanqing Zeng; Hanjia Lyu; Diyi Hu; Yinglong Xia; Jiebo Luo 001 (ICLR, 2024)

TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. - Gangda Deng; Hongkuan Zhou; Hanqing Zeng; Yinglong Xia; Christopher Leung; Jianbo Li; Rajgopal Kannan; Viktor K. Prasanna (IPDPS, 2024)

RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. - Song Jiang 002; Zahra Shakeri; Aaron Chan; Maziar Sanjabi; Hamed Firooz; Yinglong Xia; Bugra Akyildiz; Yizhou Sun; Jinchao Li; Qifan Wang 001; Asli Celikyilmaz (NAACL-HLT, 2024)

LLM-Rec: Personalized Recommendation via Prompting Large Language Models. - Hanjia Lyu; Song Jiang 002; Hanqing Zeng; Yinglong Xia; Qifan Wang 001; Si Zhang; Ren Chen; Christopher Leung; Jiajie Tang; Jiebo Luo 001 (NAACL-HLT (Findings), 2024)

Retrieval Augmentation via User Interest Clustering. - Hanjia Lyu; Hanqing Zeng; Yinglong Xia; Ren Chen; Jiebo Luo 001 (CoRR, 2024)

Discovering and Maintaining the Best $k$k in Core Decomposition. - Deming Chu; Fan Zhang 036; Wenjie Zhang 001; Xuemin Lin 001; Ying Zhang 001; Yinglong Xia; Chenyi Zhang 002 (IEEE Trans. Knowl. Data Eng., 2024)

Retrieval-Augmented Generation with Graphs (GraphRAG). - Haoyu Han 001; Yu Wang 160; Harry Shomer; Kai Guo 003; Jiayuan Ding; Yongjia Lei; Mahantesh Halappanavar; Ryan A. Rossi; Subhabrata Mukherjee; Xianfeng Tang; Qi He 002; Zhigang Hua; et al. (CoRR, 2025)

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey. - Bo Ni; Zheyuan Liu 010; Leyao Wang; Yongjia Lei; Yuying Zhao; Xueqi Cheng; Qingkai Zeng 001; Luna Dong; Yinglong Xia; Krishnaram Kenthapadi; Ryan A. Rossi; Franck Dernoncourt; et al. (CoRR, 2025)

S'MoRE: Structural Mixture of Residual Experts for LLM Fine-tuning. - Hanqing Zeng; Yinglong Xia; Zhuokai Zhao; Gilbert Jiang; Qiang Zhang; Jiayi Liu; Lizhu Zhang; Xiangjun Fan; Benyu Zhang (CoRR, 2025)