XQzip: Querying Compressed XML Using Structural Indexing. - James Cheng; Wilfred Ng (EDBT, 2004)

An Efficient Approach to Support Querying Secure Outsourced XML Information. - Yin Yang; Wilfred Ng; Ho Lam Lau; James Cheng (CAiSE, 2006)

MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining. - Yiping Ke; James Cheng; Wilfred Ng (ICDE, 2006)

delta-Tolerance Closed Frequent Itemsets. - James Cheng; Yiping Ke; Wilfred Ng (ICDM, 2006)

Mining quantitative correlated patterns using an information-theoretic approach. - Yiping Ke; James Cheng; Wilfred Ng (KDD, 2006)

Maintaining Frequent Itemsets over High-Speed Data Streams. - James Cheng; Yiping Ke; Wilfred Ng (PAKDD, 2006)

Comparative Analysis of XML Compression Technologies. - Wilfred Ng; Wai Yeung Lam; James Cheng (World Wide Web, 2006)

A Development of Hash-Lookup Trees to Support Querying Streaming XML. - James Cheng; Wilfred Ng (DASFAA, 2007)

Mining Vague Association Rules. - An Lu; Yiping Ke; James Cheng; Wilfred Ng (DASFAA, 2007)

An Efficient Index Lattice for XML Query Evaluation. - Wilfred Ng; James Cheng (DASFAA, 2007)

Correlation search in graph databases. - Yiping Ke; James Cheng; Wilfred Ng (KDD, 2007)

Fg-index: towards verification-free query processing on graph databases. - James Cheng; Yiping Ke; Wilfred Ng; An Lu (SIGMOD Conference, 2007)

Effective elimination of redundant association rules. - James Cheng; Yiping Ke; Wilfred Ng (Data Min. Knowl. Discov., 2008)

Maintaining frequent closed itemsets over a sliding window. - James Cheng; Yiping Ke; Wilfred Ng (J. Intell. Inf. Syst., 2008)

A survey on algorithms for mining frequent itemsets over data streams. - James Cheng; Yiping Ke; Wilfred Ng (Knowl. Inf. Syst., 2008)

An information-theoretic approach to quantitative association rule mining. - Yiping Ke; James Cheng; Wilfred Ng (Knowl. Inf. Syst., 2008)

Efficient Correlation Search from Graph Databases. - Yiping Ke; James Cheng; Wilfred Ng (IEEE Trans. Knowl. Data Eng., 2008)

Correlated pattern mining in quantitative databases. - Yiping Ke; James Cheng; Wilfred Ng (ACM Trans. Database Syst., 2008)

Efficient processing of group-oriented connection queries in a large graph. - James Cheng; Yiping Ke; Wilfred Ng (CIKM, 2009)

Context-Aware Object Connection Discovery in Large Graphs. - James Cheng; Yiping Ke; Wilfred Ng; Jeffrey Xu Yu (ICDE, 2009)

Efficient Discovery of Frequent Correlated Subgraph Pairs. - Yiping Ke; James Cheng; Jeffrey Xu Yu (ICDM, 2009)

Top-k Correlative Graph Mining. - Yiping Ke; James Cheng; Jeffrey Xu Yu (SDM, 2009)

Efficient query processing on graph databases. - James Cheng; Yiping Ke; Wilfred Ng (ACM Trans. Database Syst., 2009)

Querying Large Graph Databases. - Yiping Ke; James Cheng; Jeffrey Xu Yu (DASFAA (2), 2010)

K-isomorphism: privacy preserving network publication against structural attacks. - James Cheng; Ada Wai-Chee Fu; Jia Liu (SIGMOD Conference, 2010)

Finding maximal cliques in massive networks by H*-graph. - James Cheng; Yiping Ke; Ada Wai-Chee Fu; Jeffrey Xu Yu; Linhong Zhu (SIGMOD Conference, 2010)

GBLENDER: towards blending visual query formulation and query processing in graph databases. - Changjiu Jin; Sourav S. Bhowmick; Xiaokui Xiao; James Cheng; Byron Choi (SIGMOD Conference, 2010)

Efficient core decomposition in massive networks. - James Cheng; Yiping Ke; Shumo Chu; M. Tamer Özsu (ICDE, 2011)

Triangle listing in massive networks and its applications. - Shumo Chu; James Cheng (KDD, 2011)

Structure and attribute index for approximate graph matching in large graphs. - Linhong Zhu; Wee Keong Ng; James Cheng (Inf. Syst., 2011)

Finding maximal cliques in massive networks. - James Cheng; Yiping Ke; Ada Wai-Chee Fu; Jeffrey Xu Yu; Linhong Zhu (ACM Trans. Database Syst., 2011)

Fast graph query processing with a low-cost index. - James Cheng; Yiping Ke; Ada Wai-Chee Fu; Jeffrey Xu Yu (VLDB J., 2011)

Efficient algorithms for generalized subgraph query processing. - Wenqing Lin; Xiaokui Xiao; James Cheng; Sourav S. Bhowmick (CIKM, 2012)

Fast algorithms for maximal clique enumeration with limited memory. - James Cheng; Linhong Zhu; Yiping Ke; Shumo Chu (KDD, 2012)

Efficient processing of distance queries in large graphs: a vertex cover approach. - James Cheng; Yiping Ke; Shumo Chu; Carter Cheng (SIGMOD Conference, 2012)

A model-based approach to attributed graph clustering. - Zhiqiang Xu 003; Yiping Ke; Yi Wang 006; Hong Cheng 001; James Cheng (SIGMOD Conference, 2012)

IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying on Large Graphs - Ada Wai-Chee Fu; Huanhuan Wu; James Cheng; Shumo Chu; Raymond Chi-Wing Wong (CoRR, 2012)

K-Reach: Who is in Your Small World. - James Cheng; Zechao Shang; Hong Cheng 001; Haixun Wang; Jeffrey Xu Yu (Proc. VLDB Endow., 2012)

Truss Decomposition in Massive Networks. - Jia Wang; James Cheng (Proc. VLDB Endow., 2012)

Triangle listing in massive networks. - Shumo Chu; James Cheng (ACM Trans. Knowl. Discov. Data, 2012)

Finding distance-preserving subgraphs in large road networks. - Da Yan 001; James Cheng; Wilfred Ng; Steven Liu (ICDE, 2013)

Redundancy-aware maximal cliques. - Jia Wang; James Cheng; Ada Wai-Chee Fu (KDD, 2013)

TF-Label: a topological-folding labeling scheme for reachability querying in a large graph. - James Cheng; Silu Huang; Huanhuan Wu; Ada Wai-Chee Fu (SIGMOD Conference, 2013)

IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying. - Ada Wai-Chee Fu; Huanhuan Wu; James Cheng; Raymond Chi-Wing Wong (Proc. VLDB Endow., 2013)

Generalized Higher-Order Tensor Decomposition via Parallel ADMM. - Fanhua Shang; Yuanyuan Liu 001; James Cheng (AAAI, 2014)

Rectangle Counting in Large Bipartite Graphs. - Jia Wang; Ada Wai-Chee Fu; James Cheng (BigData Congress, 2014)

Distributed Maximal Clique Computation. - Yanyan Xu 005; James Cheng; Ada Wai-Chee Fu; Yingyi Bu (BigData Congress, 2014)

Robust Principal Component Analysis with Missing Data. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Hong Cheng 001 (CIKM, 2014)

Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach. - Zhou Zhao 001; James Cheng; Wilfred Ng (CIKM, 2014)

SocialTransfer: Transferring Social Knowledge for Cold-Start Cowdsourcing. - Zhou Zhao 001; James Cheng; Furu Wei; Ming Zhou 001; Wilfred Ng; Yingjun Wu (CIKM, 2014)

Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Hong Cheng 001 (ICDM, 2014)

Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. - Yuanyuan Liu 001; Fanhua Shang; Wei Fan 001; James Cheng; Hong Cheng 001 (NIPS, 2014)

Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. - Yuanyuan Liu 001; Fanhua Shang; Hong Cheng 001; James Cheng; Hanghang Tong (SDM, 2014)

Tripartite graph clustering for dynamic sentiment analysis on social media. - Linhong Zhu; Aram Galstyan; James Cheng; Kristina Lerman (SIGMOD Conference, 2014)

Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. - Yuanyuan Liu 001; Fanhua Shang; Hong Cheng 001; James Cheng (UAI, 2014)

Temporal Graph Traversals: Definitions, Algorithms, and Applications. - Silu Huang; James Cheng; Huanhuan Wu (CoRR, 2014)

Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks. - Minhao Jiang; Ada Wai-Chee Fu; Raymond Chi-Wing Wong; James Cheng; Yanyan Xu 005 (CoRR, 2014)

Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations. - Fanhua Shang; Yuanyuan Liu 001; Hanghang Tong; James Cheng; Hong Cheng 001 (CoRR, 2014)

Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation. - Yi Lu 010; James Cheng; Da Yan 001; Huanhuan Wu (Proc. VLDB Endow., 2014)

Path Problems in Temporal Graphs. - Huanhuan Wu; James Cheng; Silu Huang; Yiping Ke; Yi Lu 010; Yanyan Xu 005 (Proc. VLDB Endow., 2014)

Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs. - Da Yan 001; James Cheng; Yi Lu 010; Wilfred Ng (Proc. VLDB Endow., 2014)

Pregel Algorithms for Graph Connectivity Problems with Performance Guarantees. - Da Yan 001; James Cheng; Kai Xing; Yi Lu 010; Wilfred Ng; Yingyi Bu (Proc. VLDB Endow., 2014)

GBAGC: A General Bayesian Framework for Attributed Graph Clustering. - Zhiqiang Xu 003; Yiping Ke; Yi Wang 006; Hong Cheng 001; James Cheng (ACM Trans. Knowl. Discov. Data, 2014)

Efficient processing of k-hop reachability queries. - James Cheng; Zechao Shang; Hong Cheng 001; Haixun Wang; Jeffrey Xu Yu (VLDB J., 2014)

Core decomposition in large temporal graphs. - Huanhuan Wu; James Cheng; Yi Lu 010; Yiping Ke; Yuzhen Huang; Da Yan 001; Hejun Wu (IEEE BigData, 2015)

Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation. - Da Yan 001; James Cheng; Yi Lu 010; Wilfred Ng (WWW, 2015)

Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Hong Cheng 001 (CoRR, 2015)

Robust bilinear factorization with missing and grossly corrupted observations. - Fanhua Shang; Yuanyuan Liu 001; Hanghang Tong; James Cheng; Hong Cheng 001 (Inf. Sci., 2015)

Fast PageRank approximation by adaptive sampling. - Wenting Liu; Guangxia Li; James Cheng (Knowl. Inf. Syst., 2015)

Efficient location-based search of trajectories with location importance. - Da Yan 001; James Cheng; Zhou Zhao 001; Wilfred Ng (Knowl. Inf. Syst., 2015)

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data. - Yuanyuan Liu 001; Fanhua Shang; Licheng Jiao; James Cheng; Hong Cheng 001 (IEEE Trans. Cybern., 2015)

Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. - Fanhua Shang; Yuanyuan Liu 001; James Cheng (AAAI, 2016)

Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. - Fanhua Shang; Yuanyuan Liu 001; James Cheng (AISTATS, 2016)

SGraph: A Distributed Streaming System for Processing Big Graphs. - Cheng Chen; Hejun Wu; Dyce Jing Zhao; Da Yan 001; James Cheng (BigCom, 2016)

A comparison of general-purpose distributed systems for data processing. - Jinfeng Li; James Cheng; Yunjian Zhao; Fan Yang 091; Yuzhen Huang; Haipeng Chen 002; Ruihao Zhao (IEEE BigData, 2016)

Reachability and time-based path queries in temporal graphs. - Huanhuan Wu; Yuzhen Huang; James Cheng; Jinfeng Li; Yiping Ke (ICDE, 2016)

Diversified Temporal Subgraph Pattern Mining. - Yi Yang 029; Da Yan 001; Huanhuan Wu; James Cheng; Shuigeng Zhou; John C. S. Lui (KDD, 2016)

Big Graph Analytics Systems. - Da Yan 001; Yingyi Bu; Yuanyuan Tian 001; Amol Deshpande; James Cheng (SIGMOD Conference, 2016)

Quegel: A General-Purpose System for Querying Big Graphs. - Qizhen Zhang 001; Da Yan 001; James Cheng (SIGMOD Conference, 2016)

End-to-End Java Security Performance Enhancements for Oracle SPARC Servers. - Luyang Wang; Pallab Bhattacharya; Yao-Min Chen; Shrinivas Joshi; James Cheng (ICPE, 2016)

Unified Scalable Equivalent Formulations for Schatten Quasi-Norms. - Fanhua Shang; Yuanyuan Liu 001; James Cheng (CoRR, 2016)

Efficient Processing of Reachability and Time-Based Path Queries in a Temporal Graph. - Huanhuan Wu; Yuzhen Huang; James Cheng; Jinfeng Li; Yiping Ke (CoRR, 2016)

Quegel: A General-Purpose Query-Centric Framework for Querying Big Graphs. - Da Yan 001; James Cheng; M. Tamer Özsu; Fan Yang 091; Yi Lu 010; John C. S. Lui; Qizhen Zhang 001; Wilfred Ng (CoRR, 2016)

Lightweight Fault Tolerance in Large-Scale Distributed Graph Processing. - Da Yan 001; James Cheng; Fan Yang 091 (CoRR, 2016)

Efficient Processing of Very Large Graphs in a Small Cluster. - Da Yan 001; Yuzhen Huang; James Cheng; Huanhuan Wu (CoRR, 2016)

A General-Purpose Query-Centric Framework for Querying Big Graphs. - Da Yan 001; James Cheng; M. Tamer Özsu; Fan Yang 091; Yi Lu 010; John C. S. Lui; Qizhen Zhang 001; Wilfred Ng (Proc. VLDB Endow., 2016)

Husky: Towards a More Efficient and Expressive Distributed Computing Framework. - Fan Yang 091; Jinfeng Li; James Cheng (Proc. VLDB Endow., 2016)

Efficient Algorithms for Temporal Path Computation. - Huanhuan Wu; James Cheng; Yiping Ke; Silu Huang; Yuzhen Huang; Hejun Wu (IEEE Trans. Knowl. Data Eng., 2016)

Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition. - Yuanyuan Liu 001; Fanhua Shang; Wei Fan 001; James Cheng; Hong Cheng 001 (IEEE Trans. Neural Networks Learn. Syst., 2016)

Distributed Maximal Clique Computation and Management. - Yanyan Xu 005; James Cheng; Ada Wai-Chee Fu (IEEE Trans. Serv. Comput., 2016)

Accelerated Variance Reduced Stochastic ADMM. - Yuanyuan Liu 001; Fanhua Shang; James Cheng (AAAI, 2017)

Architectural implications on the performance and cost of graph analytics systems. - Qizhen Zhang 001; Hongzhi Chen; Da Yan 001; James Cheng; Boon Thau Loo; Purushotham V. Bangalore (SoCC, 2017)

Efficient Processing of Growing Temporal Graphs. - Huanhuan Wu; Yunjian Zhao; James Cheng; Da Yan 001 (DASFAA (2), 2017)

Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. - Yuanyuan Liu 001; Fanhua Shang; James Cheng; Hong Cheng 001; Licheng Jiao (NIPS, 2017)

LoSHa: A General Framework for Scalable Locality Sensitive Hashing. - Jinfeng Li; James Cheng; Fan Yang 091; Yuzhen Huang; Yunjian Zhao; Xiao Yan 002; Ruihao Zhao (SIGIR, 2017)

The Best of Both Worlds: Big Data Programming with Both Productivity and Performance. - Fan Yang 091; Yuzhen Huang; Yunjian Zhao; Jinfeng Li; Guanxian Jiang; James Cheng (SIGMOD Conference, 2017)

Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Kelvin Kai Wing Ng; Yuichi Yoshida (CoRR, 2017)

Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Jiacheng Zhuo (CoRR, 2017)

G-thinker: Big Graph Mining Made Easier and Faster. - Da Yan 001; Hongzhi Chen; James Cheng; M. Tamer Özsu; Qizhen Zhang 001; John C. S. Lui (CoRR, 2017)

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering. - Zhiqiang Xu 003; James Cheng; Xiaokui Xiao; Ryohei Fujimaki; Yusuke Muraoka (Knowl. Inf. Syst., 2017)

LFTF: A Framework for Efficient Tensor Analytics at Scale. - Fan Yang 091; Fanhua Shang; Yuzhen Huang; James Cheng; Jinfeng Li; Yunjian Zhao; Ruihao Zhao (Proc. VLDB Endow., 2017)

Systems for Big Graph Analytics - Da Yan 001; Yuanyuan Tian 001; James Cheng (Springer, 2017)

ASVRG: Accelerated Proximal SVRG. - Fanhua Shang; Licheng Jiao; Kaiwen Zhou; James Cheng; Yan Ren 002; Yufei Jin (ACML, 2018)

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. - Fanhua Shang; Yuanyuan Liu 001; Kaiwen Zhou; James Cheng; Kelvin Kai Wing Ng; Yuichi Yoshida (AISTATS, 2018)

G-Miner: an efficient task-oriented graph mining system. - Hongzhi Chen; Miao Liu 006; Yunjian Zhao; Xiao Yan 002; Da Yan 001; James Cheng (EuroSys, 2018)

Scalable De Novo Genome Assembly Using Pregel. - Da Yan 001; Hongzhi Chen; James Cheng; Zhenkun Cai; Bin Shao (ICDE, 2018)

A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. - Kaiwen Zhou; Fanhua Shang; James Cheng (ICML, 2018)

Norm-Ranging LSH for Maximum Inner Product Search. - Xiao Yan 002; Jinfeng Li; Xinyan Dai; Hongzhi Chen; James Cheng (NeurIPS, 2018)

A General and Efficient Querying Method for Learning to Hash. - Jinfeng Li; Xiao Yan 002; Jie Zhang 046; An Xu; James Cheng; Jie Liu 048; Kelvin Kai Wing Ng; Ti-Chung Cheng (SIGMOD Conference, 2018)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao (CoRR, 2018)

Norm-Range Partition: A Univiseral Catalyst for LSH based Maximum Inner Product Search (MIPS). - Xiao Yan 002; Xinyan Dai; Jie Liu 048; Kaiwen Zhou; James Cheng (CoRR, 2018)

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. - Fanhua Shang; James Cheng; Yuanyuan Liu 001; Zhi-Quan Luo; Zhouchen Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

FlexPS: Flexible Parallelism Control in Parameter Server Architecture. - Yuzhen Huang; Tatiana Jin; Yidi Wu; Zhenkun Cai; Xiao Yan 002; Fan Yang 091; Jinfeng Li; Yuying Guo; James Cheng (Proc. VLDB Endow., 2018)

Fuzzy Double Trace Norm Minimization for Recommendation Systems. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Da Yan 001 (IEEE Trans. Fuzzy Syst., 2018)

GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit. - Da Yan 001; Yuzhen Huang; Miao Liu 006; Hongzhi Chen; James Cheng; Huanhuan Wu; Chengcui Zhang (IEEE Trans. Parallel Distributed Syst., 2018)

Direct Acceleration of SAGA using Sampled Negative Momentum. - Kaiwen Zhou; Qinghua Ding; Fanhua Shang; James Cheng; Danli Li; Zhi-Quan Luo (AISTATS, 2019)

Pyramid: A General Framework for Distributed Similarity Search on Large-scale Datasets. - Shiyuan Deng; Xiao Yan 002; Kelvin Kai Wing Ng; Chenyu Jiang; James Cheng (IEEE BigData, 2019)

Grasper: A High Performance Distributed System for OLAP on Property Graphs. - Hongzhi Chen; Changji Li; Juncheng Fang; Chenghuan Huang; James Cheng; Jie Zhang 046; Yifan Hou; Xiao Yan 002 (SoCC, 2019)

Lightweight Fault Tolerance in Pregel-Like Systems. - Da Yan 001; James Cheng; Hongzhi Chen; Cheng Long 001; Purushotham V. Bangalore (ICPP, 2019)

A Representation Learning Framework for Property Graphs. - Yifan Hou; Hongzhi Chen; Changji Li; James Cheng; Ming-Chang Yang (KDD, 2019)

Large Scale Graph Mining with G-Miner. - Hongzhi Chen; Xiaoxi Wang; Chenghuan Huang; Juncheng Fang; Yifan Hou; Changji Li; James Cheng (SIGMOD Conference, 2019)

Tangram: Bridging Immutable and Mutable Abstractions for Distributed Data Analytics. - Yuzhen Huang; Xiao Yan 002; Guanxian Jiang; Tatiana Jin; James Cheng; An Xu; Zhanhao Liu; Shuo Tu (USENIX ATC, 2019)

Pyramid: A General Framework for Distributed Similarity Search. - Shiyuan Deng; Xiao Yan 002; Kelvin Kai Wing Ng; Chenyu Jiang; James Cheng (CoRR, 2019)

Elastic deep learning in multi-tenant GPU cluster. - Yidi Wu; Kaihao Ma; Xiao Yan 002; Zhi Liu; James Cheng (CoRR, 2019)

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. - Xinyan Dai; Xiao Yan 002; Kelvin Kai Wing Ng; Jie Liu 048; James Cheng (CoRR, 2019)

Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. - Xinyan Dai; Xiao Yan 002; Kaiwen Zhou; Han Yang 002; Kelvin Kai Wing Ng; James Cheng; Yu Fan (CoRR, 2019)

Yugong: Geo-Distributed Data and Job Placement at Scale. - Yuzhen Huang; Yingjie Shi; Zheng Zhong; Yihui Feng; James Cheng; Jiwei Li; Haochuan Fan; Chao Li 009; Tao Guan; Jingren Zhou 001 (Proc. VLDB Endow., 2019)

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. - Xinyan Dai; Xiao Yan 002; Kelvin Kai Wing Ng; Jiu Liu; James Cheng (AAAI, 2020)

Understanding and Improving Proximity Graph Based Maximum Inner Product Search. - Jie Liu 048; Xiao Yan 002; Xinyan Dai; Zhirong Li; James Cheng; Ming-Chang Yang (AAAI, 2020)

PMD: An Optimal Transportation-Based User Distance for Recommender Systems. - Yitong Meng; Xinyan Dai; Xiao Yan 002; James Cheng; Weiwen Liu; Jun Guo 008; Benben Liao; Guangyong Chen (ECIR (2), 2020)

Improving resource utilization by timely fine-grained scheduling. - Tatiana Jin; Zhenkun Cai; Boyang Li 016; Chengguang Zheng; Guanxian Jiang; James Cheng (EuroSys, 2020)

Measuring and Improving the Use of Graph Information in Graph Neural Networks. - Yifan Hou; Jie Zhang 046; James Cheng; Kaili Ma 001; Richard T. B. Ma; Hongzhi Chen; Ming-Chang Yang (ICLR, 2020)

Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. - Qinghua Ding; Kaiwen Zhou; James Cheng (IJCAI, 2020)

Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. - Kaiwen Zhou; Anthony Man-Cho So; James Cheng (NeurIPS, 2020)

Convolutional Embedding for Edit Distance. - Xinyan Dai; Xiao Yan 002; Kaiwen Zhou; Yuxuan Wang; Han Yang 002; James Cheng (SIGIR, 2020)

High Performance Distributed OLAP on Property Graphs with Grasper. - Hongzhi Chen; Bowen Wu; Shiyuan Deng; Chenghuan Huang; Changji Li; Yichao Li; James Cheng (SIGMOD Conference, 2020)

Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. - Kaiwen Zhou; Yanghua Jin; Qinghua Ding; James Cheng (UAI, 2020)

Wasserstein Collaborative Filtering for Item Cold-start Recommendation. - Yitong Meng; Xiao Yan 002; Weiwen Liu; Huanhuan Wu; James Cheng (UMAP, 2020)

Edit Distance Embedding using Convolutional Neural Networks. - Xinyan Dai; Xiao Yan 002; Kaiwen Zhou; Yuxuan Wang; Han Yang 002; James Cheng (CoRR, 2020)

Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. - Han Yang 002; Xiao Yan 002; Xinyan Dai; James Cheng (CoRR, 2020)

Understanding Graph Neural Networks from Graph Signal Denoising Perspectives. - Guoji Fu; Yifan Hou; Jie Zhang 046; Kaili Ma 001; Barakeel Fanseu Kamhoua; James Cheng (CoRR, 2020)

Hierarchical Graph Matching Network for Graph Similarity Computation. - Haibo Xiu; Xiao Yan 002; Xiaoqiang Wang; James Cheng; Lei Cao (CoRR, 2020)

The item selection problem for user cold-start recommendation. - Yitong Meng; Jie Liu 048; Xiao Yan 002; James Cheng (CoRR, 2020)

Librarians and Administrators on Academic Library Impact Research: Characteristics and Perspectives. - James Cheng; Starr Hoffman (Coll. Res. Libr., 2020)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; Hongying Liu 001; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao; Licheng Jiao (IEEE Trans. Knowl. Data Eng., 2020)

Rethinking Graph Regularization for Graph Neural Networks. - Han Yang 002; Kaili Ma 001; James Cheng (AAAI, 2021)

HyperGraph Convolution Based Attributed HyperGraph Clustering. - Barakeel Fanseu Kamhoua; Lin Zhang; Kaili Ma 001; James Cheng; Bo Li 001; Bo Han 003 (CIKM, 2021)

DGCL: an efficient communication library for distributed GNN training. - Zhenkun Cai; Xiao Yan 002; Yidi Wu; Kaihao Ma; James Cheng; Fan Yu (EuroSys, 2021)

Seastar: vertex-centric programming for graph neural networks. - Yidi Wu; Kaihao Ma; Zhenkun Cai; Tatiana Jin; Boyang Li 016; Chengguang Zheng; James Cheng; Fan Yu (EuroSys, 2021)

Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. - Han Yang 002; Xiao Yan 002; Xinyan Dai; Yongqiang Chen 002; James Cheng (IJCNN, 2021)

Vertex-Centric Visual Programming for Graph Neural Networks. - Yidi Wu; Yuntao Gui; Tatiana Jin; James Cheng; Xiao Yan 002; Peiqi Yin; Yufei Cai; Bo Tang 016; Fan Yu (SIGMOD Conference, 2021)

Scaling Large Production Clusters with Partitioned Synchronization. - Yihui Feng; Zhi Liu; Yunjian Zhao; Tatiana Jin; Yidi Wu; Yang Zhang; James Cheng; Chao Li; Tao Guan (USENIX ATC, 2021)

Improving Graph Representation Learning by Contrastive Regularization. - Kaili Ma 001; Haochen Yang; Han Yang 002; Tatiana Jin; Pengfei Chen; Yongqiang Chen 002; Barakeel Fanseu Kamhoua; James Cheng (CoRR, 2021)

G-Tran: Making Distributed Graph Transactions Fast. - Hongzhi Chen; Changji Li; Chenguang Zheng; Chenghuan Huang; Juncheng Fang; James Cheng; Jie Zhang 046 (CoRR, 2021)

Local Reweighting for Adversarial Training. - Ruize Gao; Feng Liu 003; Kaiwen Zhou; Gang Niu 001; Bo Han 003; James Cheng (CoRR, 2021)

Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. - Kaiwen Zhou; Anthony Man-Cho So; James Cheng (CoRR, 2021)

Scalable De Novo Genome Assembly Using a Pregel-Like Graph-Parallel System. - Guimu Guo; Hongzhi Chen; Da Yan 001; James Cheng; Jake Y. Chen; Zechen Chong (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Timestamped State Sharing for Stream Analytics. - Yunjian Zhao; Zhi Liu; Yidi Wu; Guanxian Jiang; James Cheng; Kunlong Liu; Xiao Yan 002 (IEEE Trans. Parallel Distributed Syst., 2021)

Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. - Kaiwen Zhou; Lai Tian; Anthony Man-Cho So; James Cheng (AISTATS, 2022)

Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. - Yongqiang Chen 002; Han Yang 002; Yonggang Zhang 003; Kaili Ma 001; Tongliang Liu; Bo Han 003; James Cheng (ICLR, 2022)

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. - Ruize Gao; Jiongxiao Wang; Kaiwen Zhou; Feng Liu 003; Binghui Xie; Gang Niu 001; Bo Han 003; James Cheng (ICML, 2022)

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. - Yongqiang Chen 002; Yonggang Zhang 003; Yatao Bian; Han Yang 002; Kaili Ma 001; Binghui Xie; Tongliang Liu; Bo Han 003; James Cheng (NeurIPS, 2022)

Exact Shape Correspondence via 2D graph convolution. - Barakeel Fanseu Kamhoua; Lin Zhang; Yongqiang Chen 002; Han Yang 002; Kaili Ma 001; Bo Han 003; Bo Li 001; James Cheng (NeurIPS, 2022)

HGL: Accelerating Heterogeneous GNN Training with Holistic Representation and Optimization. - Yuntao Gui; Yidi Wu; Han Yang 002; Tatiana Jin; Boyang Li 016; Qihui Zhou; James Cheng; Fan Yu (SC, 2022)

VSGM: View-Based GPU-Accelerated Subgraph Matching on Large Graphs. - Guanxian Jiang; Qihui Zhou; Tatiana Jin; Boyang Li 016; Yunjian Zhao; Yichao Li; James Cheng (SC, 2022)

Invariance Principle Meets Out-of-Distribution Generalization on Graphs. - Yongqiang Chen 002; Yonggang Zhang 003; Han Yang 002; Kaili Ma 001; Binghui Xie; Tongliang Liu; Bo Han 003; James Cheng (CoRR, 2022)

An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. - Binghui Xie; Chenhan Jin; Kaiwen Zhou; James Cheng; Wei Meng 001 (CoRR, 2022)

Pareto Invariant Risk Minimization. - Yongqiang Chen 002; Kaiwen Zhou; Yatao Bian; Binghui Xie; Kaili Ma 001; Yonggang Zhang 003; Han Yang 002; Bo Han 003; James Cheng (CoRR, 2022)

Efficient Private SCO for Heavy-Tailed Data via Clipping. - Chenhan Jin; Kaiwen Zhou; Bo Han 003; James Cheng; Ming-Chang Yang (CoRR, 2022)

DGI: Easy and Efficient Inference for GNNs. - Peiqi Yin; Xiao Yan 002; Jinjing Zhou; Qiang Fu; Zhenkun Cai; James Cheng; Bo Tang 016; Minjie Wang (CoRR, 2022)

G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture. - Hongzhi Chen; Changji Li; Chenguang Zheng; Chenghuan Huang; Juncheng Fang; James Cheng; Jie Zhang 046 (Proc. VLDB Endow., 2022)

ByteGraph: A High-Performance Distributed Graph Database in ByteDance. - Changji Li; Hongzhi Chen; Shuai Zhang; Yingqian Hu; Chao Chen; Zhenjie Zhang; Meng Li; Xiangchen Li; Dongqing Han; Xiaohui Chen; Xudong Wang; Huiming Zhu; et al. (Proc. VLDB Endow., 2022)

ByteGNN: Efficient Graph Neural Network Training at Large Scale. - Chenguang Zheng; Hongzhi Chen; Yuxuan Cheng; Zhezheng Song; Yifan Wu 002; Changji Li; James Cheng; Hao Yang; Shuai Zhang (Proc. VLDB Endow., 2022)

RACE: One-sided RDMA-conscious Extendible Hashing. - Pengfei Zuo; Qihui Zhou; Jiazhao Sun; Liu Yang; Shuangwu Zhang; Yu Hua 001; James Cheng; Rongfeng He; Huabing Yan (ACM Trans. Storage, 2022)

TensorOpt: Exploring the Tradeoffs in Distributed DNN Training With Auto-Parallelism. - Zhenkun Cai; Xiao Yan 002; Kaihao Ma; Yidi Wu; Yuzhen Huang; James Cheng; Teng Su; Fan Yu (IEEE Trans. Parallel Distributed Syst., 2022)

Elastic Deep Learning in Multi-Tenant GPU Clusters. - Yidi Wu; Kaihao Ma; Xiao Yan 002; Zhi Liu; Zhenkun Cai; Yuzhen Huang; James Cheng; Han Yuan; Fan Yu (IEEE Trans. Parallel Distributed Syst., 2022)

Graph Feature Management: Impact, Challenges and Opportunities. - James Cheng (GRADES-NDA@SIGMOD, 2023)

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. - Yongqiang Chen 002; Kaiwen Zhou; Yatao Bian; Binghui Xie; Bingzhe Wu; Yonggang Zhang 003; Kaili Ma 001; Han Yang 002; Peilin Zhao; Bo Han 003; James Cheng (ICLR, 2023)

DGI: An Easy and Efficient Framework for GNN Model Evaluation. - Peiqi Yin; Xiao Yan 002; Jinjing Zhou; Qiang Fu; Zhenkun Cai; James Cheng; Bo Tang 016; Minjie Wang (KDD, 2023)

Does Invariant Graph Learning via Environment Augmentation Learn Invariance? - Yongqiang Chen 002; Yatao Bian; Kaiwen Zhou; Binghui Xie; Bo Han 003; James Cheng (NeurIPS, 2023)

Understanding and Improving Feature Learning for Out-of-Distribution Generalization. - Yongqiang Chen 002; Wei Huang; Kaiwen Zhou; Yatao Bian; Bo Han 003; James Cheng (NeurIPS, 2023)

DSP: Efficient GNN Training with Multiple GPUs. - Zhenkun Cai; Qihui Zhou; Xiao Yan 002; Da Zheng; Xiang Song 003; Chenguang Zheng; James Cheng; George Karypis (PPoPP, 2023)

Towards Understanding Feature Learning in Out-of-Distribution Generalization. - Yongqiang Chen 002; Wei Huang; Kaiwen Zhou; Yatao Bian; Bo Han 003; James Cheng (CoRR, 2023)

Towards out-of-distribution generalizable predictions of chemical kinetics properties. - Zihao Wang 001; Yongqiang Chen 002; Yang Duan; Weijiang Li; Bo Han 003; James Cheng; Hanghang Tong (CoRR, 2023)

Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. - Yongqiang Chen 002; Binghui Xie; Kaiwen Zhou; Bo Han 003; Yatao Bian; James Cheng (CoRR, 2023)

SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification. - Yuntao Gui; Xiao Yan 002; Peiqi Yin; Han Yang 002; James Cheng (CoRR, 2023)

Circinus: Fast Redundancy-Reduced Subgraph Matching. - Tatiana Jin; Boyang Li 016; Yichao Li; Qihui Zhou; Qianli Ma 003; Yunjian Zhao; Hongzhi Chen; James Cheng (Proc. ACM Manag. Data, 2023)

FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication. - Kaihao Ma; Xiao Yan 002; Zhenkun Cai; Yuzhen Huang; Yidi Wu; James Cheng (Proc. ACM Manag. Data, 2023)

Calibrating and Improving Graph Contrastive Learning. - Kaili Ma 001; Garry Yang; Han Yang 002; Yongqiang Chen 002; James Cheng (Trans. Mach. Learn. Res., 2023)

GRACE: A General Graph Convolution Framework for Attributed Graph Clustering. - Barakeel Fanseu Kamhoua; Lin Zhang; Kaili Ma 001; James Cheng; Bo Li 001; Bo Han 003 (ACM Trans. Knowl. Discov. Data, 2023)

Enhancing Evolving Domain Generalization through Dynamic Latent Representations. - Binghui Xie; Yongqiang Chen 002; Jiaqi Wang 012; Kaiwen Zhou; Bo Han 003; Wei Meng 001; James Cheng (AAAI, 2024)

Follower Agnostic Learning in Stackelberg Games. - Chinmay Maheshwari; James Cheng; Shankar Sastry 001; Lillian J. Ratliff; Eric Mazumdar (CDC, 2024)

Wings: Efficient Online Multiple Graph Pattern Matching. - Guanxian Jiang; Yunjian Zhao; Yichao Li; Zhi Liu; Tatiana Jin; Wanying Zheng; Boyang Li 016; James Cheng (ICDE, 2024)

Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. - Binghui Xie; Yatao Bian; Kaiwen Zhou; Yongqiang Chen 002; Peilin Zhao; Bo Han 003; Wei Meng 001; James Cheng (ICLR, 2024)

How Interpretable Are Interpretable Graph Neural Networks? - Yongqiang Chen 002; Yatao Bian; Bo Han 003; James Cheng (ICML, 2024)

Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods. - Da Yan 001; Lyuheng Yuan; Akhlaque Ahmad; Chenguang Zheng; Hongzhi Chen; James Cheng (KDD, 2024)

Discovery of the Hidden World with Large Language Models. - Chenxi Liu; Yongqiang Chen 002; Tongliang Liu; Mingming Gong; James Cheng; Bo Han 003; Kun Zhang 001 (NeurIPS, 2024)

HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection. - Binghui Xie; Yixuan Wang; Yongqiang Chen 002; Kaiwen Zhou; Yu Li; Wei Meng 001; James Cheng (NeurIPS, 2024)

Detecting and Understanding Self-Deleting JavaScript Code. - Xinzhe Wang; Zeyang Zhuang; Wei Meng 001; James Cheng (WWW, 2024)

HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. - Yongqiang Chen 002; Quanming Yao; Juzheng Zhang; James Cheng; Yatao Bian (CoRR, 2024)

Solving the non-submodular network collapse problems via Decision Transformer. - Kaili Ma 001; Han Yang 002; Shanchao Yang; Kangfei Zhao; Lanqing Li; Yongqiang Chen 002; Junzhou Huang; James Cheng; Yu Rong 001 (Neural Networks, 2024)

GE2: A General and Efficient Knowledge Graph Embedding Learning System. - Chenguang Zheng; Guanxian Jiang; Xiao Yan 002; Peiqi Yin; Qihui Zhou; James Cheng (Proc. ACM Manag. Data, 2024)

PPS: Fair and efficient black-box scheduling for multi-tenant GPU clusters. - Kaihao Ma; Zhenkun Cai; Xiao Yan 002; Yang Zhang; Zhi Liu; Yihui Feng; Chao Li; Wei Lin; James Cheng (Parallel Comput., 2024)

Atom: An Efficient Query Serving System for Embedding-based Knowledge Graph Reasoning with Operator-level Batching. - Qihui Zhou; Peiqi Yin; Xiao Yan 002; Changji Li; Guanxian Jiang; James Cheng (Proc. ACM Manag. Data, 2024)

Efficient private SCO for heavy-tailed data via averaged clipping. - Chenhan Jin; Kaiwen Zhou; Bo Han 003; James Cheng; Tieyong Zeng (Mach. Learn., 2024)

BrainOOD: Out-of-distribution Generalizable Brain Network Analysis. - Jiaxing Xu; Yongqiang Chen; Xia Dong; Mengcheng Lan; Tiancheng Huang; Qingtian Bian; James Cheng; Yiping Ke (ICLR, 2025)

Adaptive Parallel Training for Graph Neural Networks. - Kaihao Ma; Renjie Liu 001; Xiao Yan 002; Zhenkun Cai; Xiang Song 003; Minjie Wang; Yichao Li; James Cheng (PPoPP, 2025)

DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization. - Jiaqi Wang 012; Yuhang Zhou; Zhixiong Zhang; Qiguang Chen; Yongqiang Chen 002; James Cheng (Trans. Mach. Learn. Res., 2025)

Oversmoothing as Loss of Sign: Towards Structural Balance in Graph Neural Networks. - Jiaqi Wang 012; Xinyi Wu; James Cheng; Yifei Wang (CoRR, 2025)

Progressive Sparse Attention: Algorithm and System Co-design for Efficient Attention in LLM Serving. - Qihui Zhou; Peiqi Yin; Pengfei Zuo; James Cheng (CoRR, 2025)

Retrieval-Augmented Generation with Hierarchical Knowledge. - Haoyu Huang; Yongfeng Huang; Junjie Yang; Zhenyu Pan; Yongqiang Chen 002; Kaili Ma 001; Hongzhi Chen; James Cheng (CoRR, 2025)

PilotANN: Memory-Bounded GPU Acceleration for Vector Search. - Yuntao Gui; Peiqi Yin; Xiao Yan; Chaorui Zhang; Weixi Zhang; James Cheng (CoRR, 2025)

On the Thinking-Language Modeling Gap in Large Language Models. - Chenxi Liu; Yongqiang Chen 002; Tongliang Liu; James Cheng; Bo Han 003; Kun Zhang 001 (CoRR, 2025)

Think or Not? Selective Reasoning via Reinforcement Learning for Vision-Language Models. - Jiaqi Wang; Kevin Qinghong Lin; James Cheng; Mike Zheng Shou (CoRR, 2025)

Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation. - Deyu Zou; Yongqiang Chen; Mufei Li; Siqi Miao 001; Chenxi Liu; Bo Han; James Cheng; Pan Li 005 (CoRR, 2025)

CARINA: An Efficient CXL-Oriented Embedding Serving System for Recommendation Models. - Peiqi Yin; Qihui Zhou; Xiao Yan 002; Chao Wang 125; Eric Lo 001; Changji Li; Lan Lu; Hua Fan 002; Wenchao Zhou; Ming-Chang Yang; James Cheng (Proc. ACM Manag. Data, 2025)

Towards Efficient and Scalable Distributed Vector Search with RDMA. - Xiangyu Zhi; Meng Chen; Xiao Yan; Baotong Lu; Hui Li; Qianxi Zhang; Qi Chen; James Cheng (CoRR, 2025)

Gorgeous: Revisiting the Data Layout for Disk-Resident High-Dimensional Vector Search. - Peiqi Yin; Xiao Yan; Qihui Zhou; Hui Li; Xiaolu Li; Lin Zhang; Meiling Wang; Xin Yao; James Cheng (CoRR, 2025)