James Cheng

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 151

Top Venues

Publications

Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. AAAI (2024)
Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian
HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. CoRR (2024)
Xinzhe Wang, Zeyang Zhuang, Wei Meng, James Cheng
Detecting and Understanding Self-Deleting JavaScript Code. WWW (2024)
Da Yan, Lyuheng Yuan, Akhlaque Ahmad, Chenguang Zheng, Hongzhi Chen, James Cheng
Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods. KDD (2024)
Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
How Interpretable Are Interpretable Graph Neural Networks? CoRR (2024)
Kaihao Ma, Zhenkun Cai, Xiao Yan, Yang Zhang, Zhi Liu, Yihui Feng, Chao Li, Wei Lin, James Cheng
PPS: Fair and efficient black-box scheduling for multi-tenant GPU clusters. Parallel Comput. 120 (2024)
Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR (2024)
Guanxian Jiang, Yunjian Zhao, Yichao Li, Zhi Liu, Tatiana Jin, Wanying Zheng, Boyang Li, James Cheng
Wings: Efficient Online Multiple Graph Pattern Matching. ICDE (2024)
Chenguang Zheng, Guanxian Jiang, Xiao Yan, Peiqi Yin, Qihui Zhou, James Cheng
: A General and Efficient Knowledge Graph Embedding Learning System. Proc. ACM Manag. Data 2 (3) (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR (2024)
Kaili Ma, Han Yang, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng, Yu Rong
Solving the non-submodular network collapse problems via Decision Transformer. Neural Networks 176 (2024)
Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang
Discovery of the Hidden World with Large Language Models. CoRR (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR (2024)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR (2023)
Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
GRACE: A General Graph Convolution Framework for Attributed Graph Clustering. ACM Trans. Knowl. Discov. Data 17 (3) (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR (2023)
Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis
DSP: Efficient GNN Training with Multiple GPUs. PPoPP (2023)
Tatiana Jin, Boyang Li, Yichao Li, Qihui Zhou, Qianli Ma, Yunjian Zhao, Hongzhi Chen, James Cheng
Circinus: Fast Redundancy-Reduced Subgraph Matching. Proc. ACM Manag. Data 1 (1) (2023)
Kaili Ma, Garry Yang, Han Yang, Yongqiang Chen, James Cheng
Calibrating and Improving Graph Contrastive Learning. Trans. Mach. Learn. Res. 2023 (2023)
Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong
Towards out-of-distribution generalizable predictions of chemical kinetics properties. CoRR (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS (2023)
Kaihao Ma, Xiao Yan, Zhenkun Cai, Yuzhen Huang, Yidi Wu, James Cheng
FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication. Proc. ACM Manag. Data 1 (2) (2023)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS (2023)
Yuntao Gui, Xiao Yan, Peiqi Yin, Han Yang, James Cheng
SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification. CoRR (2023)
Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR (2023)
James Cheng
Graph Feature Management: Impact, Challenges and Opportunities. GRADES-NDA@SIGMOD (2023)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR (2023)
Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang
DGI: An Easy and Efficient Framework for GNN Model Evaluation. KDD (2023)
Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng
Exact Shape Correspondence via 2D graph convolution. NeurIPS (2022)
Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang
Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR (2022)
Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang
DGI: Easy and Efficient Inference for GNNs. CoRR (2022)
Yifan Hou, Jian Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, Ming-Chang Yang
Measuring and Improving the Use of Graph Information in Graph Neural Networks. CoRR (2022)
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. ICLR (2022)
Yidi Wu, Kaihao Ma, Xiao Yan, Zhi Liu, Zhenkun Cai, Yuzhen Huang, James Cheng, Han Yuan, Fan Yu
Elastic Deep Learning in Multi-Tenant GPU Clusters. IEEE Trans. Parallel Distributed Syst. 33 (1) (2022)
Hongzhi Chen, Changji Li, Chenguang Zheng, Chenghuan Huang, Juncheng Fang, James Cheng, Jian Zhang
G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture. Proc. VLDB Endow. 15 (11) (2022)
Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. AISTATS (2022)
Chenguang Zheng, Hongzhi Chen, Yuxuan Cheng, Zhezheng Song, Yifan Wu, Changji Li, James Cheng, Hao Yang, Shuai Zhang
ByteGNN: Efficient Graph Neural Network Training at Large Scale. Proc. VLDB Endow. 15 (6) (2022)
Guanxian Jiang, Qihui Zhou, Tatiana Jin, Boyang Li, Yunjian Zhao, Yichao Li, James Cheng
VSGM: View-Based GPU-Accelerated Subgraph Matching on Large Graphs. SC (2022)
Pengfei Zuo, Qihui Zhou, Jiazhao Sun, Liu Yang, Shuangwu Zhang, Yu Hua, James Cheng, Rongfeng He, Huabing Yan
RACE: One-sided RDMA-conscious Extendible Hashing. ACM Trans. Storage 18 (2) (2022)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
Pareto Invariant Risk Minimization. CoRR (2022)
Yuntao Gui, Yidi Wu, Han Yang, Tatiana Jin, Boyang Li, Qihui Zhou, James Cheng, Fan Yu
HGL: Accelerating Heterogeneous GNN Training with Holistic Representation and Optimization. SC (2022)
Zhenkun Cai, Xiao Yan, Kaihao Ma, Yidi Wu, Yuzhen Huang, James Cheng, Teng Su, Fan Yu
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training With Auto-Parallelism. IEEE Trans. Parallel Distributed Syst. 33 (8) (2022)
Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS (2022)
Changji Li, Hongzhi Chen, Shuai Zhang, Yingqian Hu, Chao Chen, Zhenjie Zhang, Meng Li, Xiangchen Li, Dongqing Han, Xiaohui Chen, Xudong Wang, Huiming Zhu, Xuwei Fu, Tingwei Wu, Hongfei Tan, Hengtian Ding, Mengjin Liu, Kangcheng Wang, Ting Ye, Lei Li, Xin Li, Yu Wang, Chenguang Zheng, Hao Yang, James Cheng
ByteGraph: A High-Performance Distributed Graph Database in ByteDance. Proc. VLDB Endow. 15 (12) (2022)
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. CoRR (2022)
Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. CoRR (2022)
Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng
An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. CoRR (2022)
Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. ICML (2022)
Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang
A Representation Learning Framework for Property Graphs. CoRR (2022)
Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Invariance Principle Meets Out-of-Distribution Generalization on Graphs. CoRR (2022)
Han Yang, Xiao Yan, Xinyan Dai, Yongqiang Chen, James Cheng
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. IJCNN (2021)
Han Yang, Kaili Ma, James Cheng
Rethinking Graph Regularization for Graph Neural Networks. AAAI (2021)
Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
HyperGraph Convolution Based Attributed HyperGraph Clustering. CIKM (2021)
Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng
Local Reweighting for Adversarial Training. CoRR (2021)
Yidi Wu, Yuntao Gui, Tatiana Jin, James Cheng, Xiao Yan, Peiqi Yin, Yufei Cai, Bo Tang, Fan Yu
Vertex-Centric Visual Programming for Graph Neural Networks. SIGMOD Conference (2021)
Guimu Guo, Hongzhi Chen, Da Yan, James Cheng, Jake Y. Chen, Zechen Chong
Scalable De Novo Genome Assembly Using a Pregel-Like Graph-Parallel System. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (2) (2021)
Hongzhi Chen, Changji Li, Chenguang Zheng, Chenghuan Huang, Juncheng Fang, James Cheng, Jian Zhang
G-Tran: Making Distributed Graph Transactions Fast. CoRR (2021)
Yunjian Zhao, Zhi Liu, Yidi Wu, Guanxian Jiang, James Cheng, Kunlong Liu, Xiao Yan
Timestamped State Sharing for Stream Analytics. IEEE Trans. Parallel Distributed Syst. 32 (11) (2021)
Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. CoRR (2021)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. CoRR (2021)
Zhenkun Cai, Xiao Yan, Yidi Wu, Kaihao Ma, James Cheng, Fan Yu
DGCL: an efficient communication library for distributed GNN training. EuroSys (2021)
Yidi Wu, Kaihao Ma, Zhenkun Cai, Tatiana Jin, Boyang Li, Chengguang Zheng, James Cheng, Fan Yu
Seastar: vertex-centric programming for graph neural networks. EuroSys (2021)
Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng
Improving Graph Representation Learning by Contrastive Regularization. CoRR (2021)
Yihui Feng, Zhi Liu, Yunjian Zhao, Tatiana Jin, Yidi Wu, Yang Zhang, James Cheng, Chao Li, Tao Guan
Scaling Large Production Clusters with Partitioned Synchronization. USENIX Annual Technical Conference (2021)
Yifan Hou, Jian Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, Ming-Chang Yang
Measuring and Improving the Use of Graph Information in Graph Neural Networks. ICLR (2020)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. NeurIPS (2020)
James Cheng, Starr Hoffman
Librarians and Administrators on Academic Library Impact Research: Characteristics and Perspectives. Coll. Res. Libr. 81 (3) (2020)
Guoji Fu, Yifan Hou, Jian Zhang, Kaili Ma, Barakeel Fanseu Kamhoua, James Cheng
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives. CoRR (2020)
Han Yang, Xiao Yan, Xinyan Dai, James Cheng
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. CoRR (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Convolutional Embedding for Edit Distance. SIGIR (2020)
Haibo Xiu, Xiao Yan, Xiaoqiang Wang, James Cheng, Lei Cao
Hierarchical Graph Matching Network for Graph Similarity Computation. CoRR (2020)
Tatiana Jin, Zhenkun Cai, Boyang Li, Chengguang Zheng, Guanxian Jiang, James Cheng
Improving resource utilization by timely fine-grained scheduling. EuroSys (2020)
Han Yang, Kaili Ma, James Cheng
Rethinking Graph Regularization For Graph Neural Networks. CoRR (2020)
Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng
Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. UAI (2020)
Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jiu Liu, James Cheng
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. AAAI (2020)
Yitong Meng, Xinyan Dai, Xiao Yan, James Cheng, Weiwen Liu, Jun Guo, Benben Liao, Guangyong Chen
PMD: An Optimal Transportation-Based User Distance for Recommender Systems. ECIR (2) (2020)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates. CoRR (2020)
Jie Liu, Xiao Yan, Xinyan Dai, Zhirong Li, James Cheng, Ming-Chang Yang
Understanding and Improving Proximity Graph Based Maximum Inner Product Search. AAAI (2020)
Yitong Meng, Jie Liu, Xiao Yan, James Cheng
The item selection problem for user cold-start recommendation. CoRR (2020)
Hongzhi Chen, Bowen Wu, Shiyuan Deng, Chenghuan Huang, Changji Li, Yichao Li, James Cheng
High Performance Distributed OLAP on Property Graphs with Grasper. SIGMOD Conference (2020)
Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32 (1) (2020)
Qinghua Ding, Kaiwen Zhou, James Cheng
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. IJCAI (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Edit Distance Embedding using Convolutional Neural Networks. CoRR (2020)
Yitong Meng, Xiao Yan, Weiwen Liu, Huanhuan Wu, James Cheng
Wasserstein Collaborative Filtering for Item Cold-start Recommendation. UMAP (2020)
Zhenkun Cai, Kaihao Ma, Xiao Yan, Yidi Wu, Yuzhen Huang, James Cheng, Teng Su, Fan Yu
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism. CoRR (2020)
Yuzhen Huang, Xiao Yan, Guanxian Jiang, Tatiana Jin, James Cheng, An Xu, Zhanhao Liu, Shuo Tu
Tangram: Bridging Immutable and Mutable Abstractions for Distributed Data Analytics. USENIX Annual Technical Conference (2019)
Yuzhen Huang, Yingjie Shi, Zheng Zhong, Yihui Feng, James Cheng, Jiwei Li, Haochuan Fan, Chao Li, Tao Guan, Jingren Zhou
Yugong: Geo-Distributed Data and Job Placement at Scale. Proc. VLDB Endow. 12 (12) (2019)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR (2019)
Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng
Pyramid: A General Framework for Distributed Similarity Search. CoRR (2019)
Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng
Pyramid: A General Framework for Distributed Similarity Search on Large-scale Datasets. IEEE BigData (2019)
Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS (2019)
Hongzhi Chen, Xiaoxi Wang, Chenghuan Huang, Juncheng Fang, Yifan Hou, Changji Li, James Cheng
Large Scale Graph Mining with G-Miner. SIGMOD Conference (2019)
Hongzhi Chen, Changji Li, Juncheng Fang, Chenghuan Huang, James Cheng, Jian Zhang, Yifan Hou, Xiao Yan
Grasper: A High Performance Distributed System for OLAP on Property Graphs. SoCC (2019)
Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jie Liu, James Cheng
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. CoRR (2019)
Jie Liu, Xiao Yan, Xinyan Dai, Zhirong Li, James Cheng, Ming-Chang Yang
Understanding and Improving Proximity Graph based Maximum Inner Product Search. CoRR (2019)
Changji Li, Xiao Yan, Jian Zhang, James Cheng, Yifan Hou, Hongzhi Chen, Juncheng Fang, Chenghuan Huang
Grasper: A High Performance Distributed System for OLAP on Property Graphs. SoCC (2019)
Da Yan, James Cheng, Hongzhi Chen, Cheng Long, Purushotham V. Bangalore
Lightweight Fault Tolerance in Pregel-Like Systems. ICPP (2019)
Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang
A Representation Learning Framework for Property Graphs. KDD (2019)
Yidi Wu, Kaihao Ma, Xiao Yan, Zhi Liu, James Cheng
Elastic deep learning in multi-tenant GPU cluster. CoRR (2019)
Da Yan, Hongzhi Chen, James Cheng, Zhenkun Cai, Bin Shao
Scalable De Novo Genome Assembly Using Pregel. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

James Cheng