Jie Chen

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 72

Top Topics

Directed Acyclic

Money Laundering

Stochastic Gradient

Top Venues

Publications

Junyi Li, Jie Chen, Ruiyang Ren, Xiaoxue Cheng, Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. ACL (1) (2024)
Michael Sun, Minghao Guo, Weize Yuan, Veronika Thost, Crystal Elaine Owens, Aristotle Franklin Grosz, Sharvaa Selvan, Katelyn Zhou, Hassan Mohiuddin, Benjamin J. Pedretti, Zachary P. Smith, Jie Chen, Wojciech Matusik
Representing Molecules as Random Walks Over Interpretable Grammars. CoRR (2024)
Tianyi Tang, Yiwen Hu, Bingqian Li, Wenyang Luo, Zijing Qin, Haoxiang Sun, Jiapeng Wang, Shiyi Xu, Xiaoxue Cheng, Geyang Guo, Han Peng, Bowen Zheng, Yiru Tang, Yingqian Min, Yushuo Chen, Jie Chen, Yuanqian Zhao, Luran Ding, Yuhao Wang, Zican Dong, Chunxuan Xia, Junyi Li, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
LLMBox: A Comprehensive Library for Large Language Models. CoRR (2024)
Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen
The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset. CoRR (2024)
Jie Chen, Zhipeng Chen, Jiapeng Wang, Kun Zhou, Yutao Zhu, Jinhao Jiang, Yingqian Min, Wayne Xin Zhao, Zhicheng Dou, Jiaxin Mao, Yankai Lin, Ruihua Song, Jun Xu, Xu Chen, Rui Yan, Zhewei Wei, Di Hu, Wenbing Huang, Ji-Rong Wen
Towards Effective and Efficient Continual Pre-training of Large Language Models. CoRR (2024)
Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. MLSys (2023)
Xiao Zang, Jie Chen, Bo Yuan
GUAP: Graph Universal Attack Through Adversarial Patching. CoRR (2023)
Gabriel Mancino-Ball, Shengnan Miao, Yangyang Xu, Jie Chen
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization. AAAI (2023)
Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. CoRR (2023)
Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. ICML (2023)
Han Huang, Jiajia Yu, Jie Chen, Rongjie Lai
Bridging mean-field games and normalizing flows with trajectory regularization. J. Comput. Phys. 487 (2023)
Yangyang Xu, Yibo Xu, Yonggui Yan, Colin Sutcher-Shepard, Leopold Grinberg, Jie Chen
Parallel and distributed asynchronous adaptive stochastic gradient methods. Math. Program. Comput. 15 (3) (2023)
Zehao Niu, Mihai Anitescu, Jie Chen
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning. ICLR (2023)
Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. CoRR (2023)
Zehao Niu, Mihai Anitescu, Jie Chen
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning. CoRR (2023)
Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. MLSys (2022)
Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
Data-Efficient Graph Grammar Learning for Molecular Generation. ICLR (2022)
Yangyang Xu, Yibo Xu, Yonggui Yan, Jie Chen
Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems. SIAM J. Imaging Sci. 15 (2) (2022)
Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
Data-Efficient Graph Grammar Learning for Molecular Generation. CoRR (2022)
Xiao Zang, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
Noise Injection-based Regularization for Point Cloud Processing. CoRR (2021)
Tengfei Ma, Jie Chen
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. AAAI (2021)
Tim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja, Georgios Kollias
PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. APOCS (2021)
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir R. Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. NeurIPS Datasets and Benchmarks (2021)
Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. CoRR (2021)
Chao Shang, Jie Chen, Jinbo Bi
Discrete Graph Structure Learning for Forecasting Multiple Time Series. ICLR (2021)
Veronika Thost, Jie Chen
Directed Acyclic Graph Neural Networks. CoRR (2021)
Yangyang Xu, Yibo Xu, Yonggui Yan, Jie Chen
Distributed stochastic inertial methods with delayed derivatives. CoRR (2021)
Veronika Thost, Jie Chen
Directed Acyclic Graph Neural Networks. ICLR (2021)
Jie Chen, Yousef Saad, Zechen Zhang
Graph coarsening: From scientific computing to machine learning. CoRR (2021)
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir R. Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Ulrich Finkler
Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. CoRR (2021)
Yuliang Ji, Ru Huang, Jie Chen, Yuanzhe Xi
Generating a Doppelganger Graph: Resembling but Distinct. CoRR (2021)
Chao Shang, Jie Chen, Jinbo Bi
Discrete Graph Structure Learning for Forecasting Multiple Time Series. CoRR (2021)
Xiao Zang, Yi Xie, Jie Chen, Bo Yuan
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models. IJCAI (2021)
Xiao Zang, Yi Xie, Jie Chen, Bo Yuan
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models. CoRR (2020)
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B. Schardl, Charles E. Leiserson
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. AAAI (2020)
Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator. AAAI (2020)
Yangyang Xu, Colin Sutcher-Shepard, Yibo Xu, Jie Chen
Asynchronous parallel adaptive stochastic gradient methods. CoRR (2020)
Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen, Michael Katz
Online Planner Selection with Graph Neural Networks and Adaptive Scheduling. AAAI (2020)
Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
Embedding Compression with Isotropic Iterative Quantization. CoRR (2020)
Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
Embedding Compression with Isotropic Iterative Quantization. AAAI (2020)
Yue Yu, Jie Chen, Tian Gao, Mo Yu
DAG-GNN: DAG Structure Learning with Graph Neural Networks. ICML (2019)
Yue Yu, Jie Chen, Tian Gao, Mo Yu
DAG-GNN: DAG Structure Learning with Graph Neural Networks. CoRR (2019)
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI (2019)
Patrick Ferber, Tengfei Ma, Siyu Huo, Jie Chen, Michael Katz
IPC: A Benchmark Data Set for Learning with Graph-Structured Data. CoRR (2019)
Siyu Huo, Tengfei Ma, Jie Chen, Maria Chang, Lingfei Wu, Michael Witbrock
Graph Enhanced Cross-Domain Text-to-SQL Generation. TextGraphs@EMNLP (2019)
Stefan C. Schonsheck, Jie Chen, Rongjie Lai
Chart Auto-Encoders for Manifold Structured Data. CoRR (2019)
Tengfei Ma, Jie Chen
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. CoRR (2019)
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR (2019)
Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele, Claudio Bellei, Tom Robinson, Charles E. Leiserson
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. CoRR (2019)
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. CoRR (2019)
Ruslan Shaydulin, Jie Chen, Ilya Safro
Relaxation-Based Coarsening for Multilevel Hypergraph Partitioning. Multiscale Model. Simul. 17 (1) (2019)
Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator. CoRR (2019)
Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. CoRR (2018)
Jie Chen, Yousef Saad
A posteriori error estimate for computing tr(f(A)) by using the Lanczos method. Numer. Linear Algebra Appl. 25 (5) (2018)
Tengfei Ma, Jie Chen, Cao Xiao
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. CoRR (2018)
Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen, Michael Katz
Adaptive Planner Scheduling with Graph Neural Networks. CoRR (2018)
Jie Chen, Tengfei Ma, Cao Xiao
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. ICLR (Poster) (2018)
Fu Lin, Jie Chen
Learning low-complexity autoregressive models via proximal alternating minimization. Syst. Control. Lett. 122 (2018)
Jie Chen, Tengfei Ma, Cao Xiao
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. CoRR (2018)
Jie Chen, Ronny Luss
Stochastic Gradient Descent with Biased but Consistent Gradient Estimators. CoRR (2018)
Tengfei Ma, Jie Chen, Cao Xiao
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. NeurIPS (2018)
Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl
Scalable Graph Learning for Anti-Money Laundering: A First Look. CoRR (2018)
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically Compositional Kernels for Scalable Nonparametric Learning. J. Mach. Learn. Res. 18 (2017)
Ruslan Shaydulin, Jie Chen, Ilya Safro
Relaxation-Based Coarsening for Multilevel Hypergraph Partitioning. CoRR (2017)
Shashanka Ubaru, Jie Chen, Yousef Saad
Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature. SIAM J. Matrix Anal. Appl. 38 (4) (2017)
Fu Lin, Jie Chen
Learning low-complexity autoregressive models with limited time sequence data. ACC (2017)
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically Compositional Kernels for Scalable Nonparametric Learning. CoRR (2016)
Jie Chen, Lingfei Wu, Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran
Efficient one-vs-one kernel ridge regression for speech recognition. ICASSP (2016)
Jie Chen
How Accurately Should I Compute Implicit Matrix-Vector Products When Applying the Hutchinson Trace Estimator? SIAM J. Sci. Comput. 38 (6) (2016)
Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. KDD (2016)
Jie Chen, Lois C. McInnes, Hong Zhang
Analysis and Practical Use of Flexible BiCGStab. J. Sci. Comput. 68 (2) (2016)
Jie Chen, Dehua Cheng, Yan Liu
On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps. CoRR (2016)
Jie Chen, Tom L. H. Li, Mihai Anitescu
A parallel linear solver for multilevel Toeplitz systems with possibly several right-hand sides. Parallel Comput. 40 (8) (2014)
Jie Chen, Lei Wang, Mihai Anitescu
A Fast Summation Tree Code for Matérn Kernel. SIAM J. Sci. Comput. 36 (1) (2014)
Jie Chen, Tom L. H. Li
Parallelizing the Conjugate Gradient Algorithm for Multilevel Toeplitz Systems. ICCS (2013)
Jie Chen
On the Use of Discrete Laplace Operator for Preconditioning Kernel Matrices. SIAM J. Sci. Comput. 35 (2) (2013)
Jie Chen, Yousef Saad
Dense Subgraph Extraction with Application to Community Detection. IEEE Trans. Knowl. Data Eng. 24 (7) (2012)
Mihai Anitescu, Jie Chen, Lei Wang
A Matrix-free Approach for Solving the Parametric Gaussian Process Maximum Likelihood Problem. SIAM J. Sci. Comput. 34 (1) (2012)
Michael L. Stein, Jie Chen, Mihai Anitescu
Difference Filter Preconditioning for Large Covariance Matrices. SIAM J. Matrix Anal. Appl. 33 (1) (2012)
Effrosini Kokiopoulou, Jie Chen, Yousef Saad
Trace optimization and eigenproblems in dimension reduction methods. Numer. Linear Algebra Appl. 18 (3) (2011)
Jie Chen, Ilya Safro
A measure of the local connectivity between graph vertices. ICCS (2011)
Jie Chen, Mihai Anitescu, Yousef Saad
Computing f(A)b via Least Squares Polynomial Approximations. SIAM J. Sci. Comput. 33 (1) (2011)
Jie Chen, Ilya Safro
Algebraic Distance on Graphs. SIAM J. Sci. Comput. 33 (6) (2011)
Jie Chen, Ilya Safro
A Measure of the Connection Strengths between Graph Vertices with Applications CoRR (2009)
Jie Chen, Haw-ren Fang, Yousef Saad
NN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection. J. Mach. Learn. Res. 10 (2009)
Jie Chen, Yousef Saad
Divide and Conquer Strategies for Effective Information Retrieval. SDM (2009)
Jie Chen, Yousef Saad
Lanczos Vectors versus Singular Vectors for Effective Dimension Reduction. IEEE Trans. Knowl. Data Eng. 21 (8) (2009)
Jie Chen, Yousef Saad
On the Tensor SVD and the Optimal Low Rank Orthogonal Approximation of Tensors. SIAM J. Matrix Anal. Appl. 30 (4) (2008)
Jie Chen, Baoquan Chen
Architectural Modeling from Sparsely Scanned Range Data. Int. J. Comput. Vis. 78 (2-3) (2008)