Architectural Modeling from Sparsely Scanned Range Data. - Jie Chen 007; Baoquan Chen (Int. J. Comput. Vis., 2008)

On the Tensor SVD and the Optimal Low Rank Orthogonal Approximation of Tensors. - Jie Chen 007; Yousef Saad (SIAM J. Matrix Anal. Appl., 2008)

Divide and Conquer Strategies for Effective Information Retrieval. - Jie Chen 007; Yousef Saad (SDM, 2009)

A Measure of the Connection Strengths between Graph Vertices with Applications - Jie Chen 007; Ilya Safro (CoRR, 2009)

Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection. - Jie Chen 007; Haw-ren Fang; Yousef Saad (J. Mach. Learn. Res., 2009)

Lanczos Vectors versus Singular Vectors for Effective Dimension Reduction. - Jie Chen 007; Yousef Saad (IEEE Trans. Knowl. Data Eng., 2009)

Trace optimization and eigenproblems in dimension reduction methods. - Effrosini Kokiopoulou; Jie Chen 007; Yousef Saad (Numer. Linear Algebra Appl., 2011)

A measure of the local connectivity between graph vertices. - Jie Chen 007; Ilya Safro (ICCS, 2011)

Computing f(A)b via Least Squares Polynomial Approximations. - Jie Chen 007; Mihai Anitescu; Yousef Saad (SIAM J. Sci. Comput., 2011)

Algebraic Distance on Graphs. - Jie Chen 007; Ilya Safro (SIAM J. Sci. Comput., 2011)

Difference Filter Preconditioning for Large Covariance Matrices. - Michael L. Stein; Jie Chen 007; Mihai Anitescu (SIAM J. Matrix Anal. Appl., 2012)

A Matrix-free Approach for Solving the Parametric Gaussian Process Maximum Likelihood Problem. - Mihai Anitescu; Jie Chen 007; Lei Wang 013 (SIAM J. Sci. Comput., 2012)

Dense Subgraph Extraction with Application to Community Detection. - Jie Chen 007; Yousef Saad (IEEE Trans. Knowl. Data Eng., 2012)

Parallelizing the Conjugate Gradient Algorithm for Multilevel Toeplitz Systems. - Jie Chen 007; Tom L. H. Li (ICCS, 2013)

On the Use of Discrete Laplace Operator for Preconditioning Kernel Matrices. - Jie Chen 007 (SIAM J. Sci. Comput., 2013)

A parallel linear solver for multilevel Toeplitz systems with possibly several right-hand sides. - Jie Chen 007; Tom L. H. Li; Mihai Anitescu (Parallel Comput., 2014)

A Fast Summation Tree Code for Matérn Kernel. - Jie Chen 007; Lei Wang 013; Mihai Anitescu (SIAM J. Sci. Comput., 2014)

Efficient one-vs-one kernel ridge regression for speech recognition. - Jie Chen 007; Lingfei Wu 001; Kartik Audhkhasi; Brian Kingsbury; Bhuvana Ramabhadran (ICASSP, 2016)

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. - Lingfei Wu 001; Ian En-Hsu Yen; Jie Chen 007; Rui Yan 001 (KDD, 2016)

On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps. - Jie Chen 007; Dehua Cheng; Yan Liu 002 (CoRR, 2016)

Analysis and Practical Use of Flexible BiCGStab. - Jie Chen 007; Lois C. McInnes; Hong Zhang 006 (J. Sci. Comput., 2016)

How Accurately Should I Compute Implicit Matrix-Vector Products When Applying the Hutchinson Trace Estimator? - Jie Chen 007 (SIAM J. Sci. Comput., 2016)

Learning low-complexity autoregressive models with limited time sequence data. - Fu Lin; Jie Chen 007 (ACC, 2017)

Hierarchically Compositional Kernels for Scalable Nonparametric Learning. - Jie Chen 007; Haim Avron; Vikas Sindhwani (J. Mach. Learn. Res., 2017)

Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature. - Shashanka Ubaru; Jie Chen 007; Yousef Saad (SIAM J. Matrix Anal. Appl., 2017)

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. - Jie Chen 007; Tengfei Ma 001; Cao Xiao (ICLR (Poster), 2018)

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. - Tengfei Ma 001; Jie Chen 007; Cao Xiao (NeurIPS, 2018)

Stochastic Gradient Descent with Biased but Consistent Gradient Estimators. - Jie Chen 007; Ronny Luss (CoRR, 2018)

Adaptive Planner Scheduling with Graph Neural Networks. - Tengfei Ma 001; Patrick Ferber; Siyu Huo; Jie Chen 007; Michael Katz 001 (CoRR, 2018)

Scalable Graph Learning for Anti-Money Laundering: A First Look. - Mark Weber; Jie Chen 007; Toyotaro Suzumura; Aldo Pareja; Tengfei Ma 001; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson; Tao B. Schardl (CoRR, 2018)

A posteriori error estimate for computing tr(f(A)) by using the Lanczos method. - Jie Chen 007; Yousef Saad (Numer. Linear Algebra Appl., 2018)

Learning low-complexity autoregressive models via proximal alternating minimization. - Fu Lin; Jie Chen 007 (Syst. Control. Lett., 2018)

A Sequential Set Generation Method for Predicting Set-Valued Outputs. - Tian Gao; Jie Chen 007; Vijil Chenthamarakshan; Michael Witbrock (AAAI, 2019)

DAG-GNN: DAG Structure Learning with Graph Neural Networks. - Yue Yu; Jie Chen 007; Tian Gao; Mo Yu (ICML, 2019)

Graph Enhanced Cross-Domain Text-to-SQL Generation. - Siyu Huo; Tengfei Ma 001; Jie Chen 007; Maria Chang 001; Lingfei Wu 001; Michael Witbrock (TextGraphs@EMNLP, 2019)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson (CoRR, 2019)

IPC: A Benchmark Data Set for Learning with Graph-Structured Data. - Patrick Ferber; Tengfei Ma 001; Siyu Huo; Jie Chen 007; Michael Katz 001 (CoRR, 2019)

Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. - Mark Weber; Giacomo Domeniconi; Jie Chen 007; Daniel Karl I. Weidele; Claudio Bellei; Tom Robinson; Charles E. Leiserson (CoRR, 2019)

Chart Auto-Encoders for Manifold Structured Data. - Stefan C. Schonsheck; Jie Chen 007; Rongjie Lai (CoRR, 2019)

Relaxation-Based Coarsening for Multilevel Hypergraph Partitioning. - Ruslan Shaydulin; Jie Chen 007; Ilya Safro (Multiscale Model. Simul., 2019)

Embedding Compression with Isotropic Iterative Quantization. - Siyu Liao; Jie Chen 007; Yanzhi Wang; Qinru Qiu; Bo Yuan 001 (AAAI, 2020)

Online Planner Selection with Graph Neural Networks and Adaptive Scheduling. - Tengfei Ma 001; Patrick Ferber; Siyu Huo; Jie Chen 007; Michael Katz 001 (AAAI, 2020)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (AAAI, 2020)

CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator. - Huy Phan; Yi Xie 001; Siyu Liao; Jie Chen 007; Bo Yuan 001 (AAAI, 2020)

Asynchronous parallel adaptive stochastic gradient methods. - Yangyang Xu; Colin Sutcher-Shepard; Yibo Xu; Jie Chen 007 (CoRR, 2020)

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. - Tengfei Ma 001; Jie Chen 007 (AAAI, 2021)

PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. - Tim Kaler; Tao B. Schardl; Brian Xie; Charles E. Leiserson; Jie Chen 007; Aldo Pareja; Georgios Kollias (APOCS, 2021)

Discrete Graph Structure Learning for Forecasting Multiple Time Series. - Chao Shang; Jie Chen 007; Jinbo Bi (ICLR, 2021)

Directed Acyclic Graph Neural Networks. - Veronika Thost; Jie Chen 007 (ICLR, 2021)

Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models. - Xiao Zang; Yi Xie 001; Jie Chen 007; Bo Yuan 001 (IJCAI, 2021)

CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. - Ruchir Puri; David S. Kung 001; Geert Janssen; Wei Zhang 022; Giacomo Domeniconi; Vladimir Zolotov; Julian Dolby; Jie Chen 007; Mihir R. Choudhury; Lindsey Decker; Veronika Thost; Luca Buratti; et al. (NeurIPS Datasets and Benchmarks, 2021)

Generating a Doppelganger Graph: Resembling but Distinct. - Yuliang Ji; Ru Huang 003; Jie Chen 007; Yuanzhe Xi (CoRR, 2021)

Noise Injection-based Regularization for Point Cloud Processing. - Xiao Zang; Yi Xie 001; Siyu Liao; Jie Chen 007; Bo Yuan 001 (CoRR, 2021)

Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. - Ruchir Puri; David S. Kung 001; Geert Janssen; Wei Zhang 022; Giacomo Domeniconi; Vladimir Zolotov; Julian Dolby; Jie Chen 007; Mihir R. Choudhury; Lindsey Decker; Veronika Thost; Luca Buratti; et al. (CoRR, 2021)

Graph coarsening: From scientific computing to machine learning. - Jie Chen 007; Yousef Saad; Zechen Zhang (CoRR, 2021)

Distributed stochastic inertial methods with delayed derivatives. - Yangyang Xu; Yibo Xu; Yonggui Yan; Jie Chen 007 (CoRR, 2021)

Data-Efficient Graph Grammar Learning for Molecular Generation. - Minghao Guo; Veronika Thost; Beichen Li; Payel Das; Jie Chen 007; Wojciech Matusik (ICLR, 2022)

Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. - Tim Kaler; Nickolas Stathas; Anne Ouyang; Alexandros-Stavros Iliopoulos; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2022)

Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems. - Yangyang Xu; Yibo Xu; Yonggui Yan; Jie Chen 007 (SIAM J. Imaging Sci., 2022)

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization. - Gabriel Mancino-Ball; Shengnan Miao; Yangyang Xu; Jie Chen 007 (AAAI, 2023)

Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning. - Zehao Niu; Mihai Anitescu; Jie Chen 007 (ICLR, 2023)

Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. - Minghao Guo; Veronika Thost; Samuel W. Song; Adithya Balachandran; Payel Das; Jie Chen 007; Wojciech Matusik (ICML, 2023)

Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. - Tim Kaler; Alexandros-Stavros Iliopoulos; Philip Murzynowski; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2023)

Federated learning of models pre-trained on different features with consensus graphs. - Tengfei Ma 001; Trong Nghia Hoang; Jie Chen 007 (UAI, 2023)

GUAP: Graph Universal Attack Through Adversarial Patching. - Xiao Zang; Jie Chen 007; Bo Yuan 001 (CoRR, 2023)

Bridging mean-field games and normalizing flows with trajectory regularization. - Han Huang; Jiajia Yu; Jie Chen 007; Rongjie Lai (J. Comput. Phys., 2023)

A Decentralized Primal-Dual Framework for Non-Convex Smooth Consensus Optimization. - Gabriel Mancino-Ball; Yangyang Xu; Jie Chen 007 (IEEE Trans. Signal Process., 2023)

Parallel and distributed asynchronous adaptive stochastic gradient methods. - Yangyang Xu; Yibo Xu; Yonggui Yan; Colin Sutcher-Shepard; Leopold Grinberg; Jie Chen 007 (Math. Program. Comput., 2023)

The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. - Junyi Li; Jie Chen 007; Ruiyang Ren; Xiaoxue Cheng; Xin Zhao 018; Jian-Yun Nie; Ji-Rong Wen (ACL (1), 2024)

Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models. - Jie Chen 007; Yupeng Zhang; Bingning Wang; Xin Zhao 018; Ji-Rong Wen; Weipeng Chen (EMNLP (Findings), 2024)

Identifying Money Laundering Subgraphs on the Blockchain. - Kiwhan Song; Mohamed Ali Dhraief; Muhua Xu; Locke Cai; Xuhao Chen 001; Arvind Mithal; Jie Chen 007 (ICAIF, 2024)

Representing Molecules as Random Walks Over Interpretable Grammars. - 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 007; et al. (ICML, 2024)

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. - Yunsheng Tian; Ane Zuniga; Xinwei Zhang 001; Johannes P. Dürholt; Payel Das; Jie Chen 007; Wojciech Matusik; Mina Konakovic-Lukovic (ICML, 2024)

The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset. - Claudio Bellei; Muhua Xu; Ross Phillips; Tom Robinson; Mark Weber; Tim Kaler; Charles E. Leiserson; Arvind 001; Jie Chen 007 (CoRR, 2024)

LLMBox: A Comprehensive Library for Large Language Models. - Tianyi Tang; Yiwen Hu; Bingqian Li; Wenyang Luo; Zijing Qin; Haoxiang Sun; Jiapeng Wang; Shiyi Xu; Xiaoxue Cheng; Geyang Guo; Han Peng; Bowen Zheng 005; et al. (CoRR, 2024)

Syntax-Guided Procedural Synthesis of Molecules. - Michael Sun; Alston Lo; Wenhao Gao 001; Minghao Guo; Veronika Thost; Jie Chen 007; Connor W. Coley; Wojciech Matusik (CoRR, 2024)

Technical Report: Enhancing LLM Reasoning with Reward-guided Tree Search. - Jinhao Jiang; Zhipeng Chen 001; Yingqian Min; Jie Chen 007; Xiaoxue Cheng; Jiapeng Wang; Yiru Tang; Haoxiang Sun; Jia Deng; Wayne Xin Zhao; Zheng Liu 011; Dong Yan; et al. (CoRR, 2024)

Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems. - Yingqian Min; Zhipeng Chen 001; Jinhao Jiang; Jie Chen 007; Jia Deng; Yiwen Hu; Yiru Tang; Jiapeng Wang; Xiaoxue Cheng; Huatong Song; Wayne Xin Zhao; Zheng Liu 011; et al. (CoRR, 2024)

YuLan-Mini: An Open Data-efficient Language Model. - Yiwen Hu; Huatong Song; Jia Deng; Jiapeng Wang; Jie Chen 007; Kun Zhou 002; Yutao Zhu 001; Jinhao Jiang; Zican Dong; Wayne Xin Zhao; Ji-Rong Wen (CoRR, 2024)

GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. - Xinwei Zhang 001; Mingyi Hong 001; Jie Chen 007 (Trans. Mach. Learn. Res., 2024)

Towards Effective and Efficient Continual Pre-training of Large Language Models. - Jie Chen 007; Zhipeng Chen 001; Jiapeng Wang; Kun Zhou 002; Yutao Zhu 001; Jinhao Jiang; Yingqian Min; Xin Zhao 018; Zhicheng Dou; Jiaxin Mao; Yankai Lin; Ruihua Song; et al. (ACL (1), 2025)

YuLan-Mini: Pushing the Limits of Open Data-efficient Language Model. - Yiwen Hu; Huatong Song; Jie Chen 007; Jia Deng; Jiapeng Wang; Kun Zhou 002; Yutao Zhu 001; Jinhao Jiang; Zican Dong; Yang Lu; Xu Miao; Xin Zhao 018; et al. (ACL (1), 2025)

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning. - Gang Liu; Michael Sun; Wojciech Matusik; Meng Jiang; Jie Chen 007 (ICLR, 2025)

Procedural Synthesis of Synthesizable Molecules. - Michael Sun; Alston Lo; Minghao Guo; Jie Chen 007; Connor W. Coley; Wojciech Matusik (ICLR, 2025)

An Empirical Study on Eliciting and Improving R1-like Reasoning Models. - Zhipeng Chen 001; Yingqian Min; Beichen Zhang; Jie Chen 007; Jinhao Jiang; Daixuan Cheng; Wayne Xin Zhao; Zheng Liu 011; Xu Miao; Yang Lu; Lei Fang; Zhongyuan Wang 006; et al. (CoRR, 2025)

R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning. - Huatong Song; Jinhao Jiang; Yingqian Min; Jie Chen 007; Zhipeng Chen 001; Wayne Xin Zhao; Lei Fang; Ji-Rong Wen (CoRR, 2025)

Mixed Precision Orthogonalization-Free Projection Methods for Eigenvalue and Singular Value Problems. - Tianshi Xu; Zechen Zhang; Jie Chen 007; Yousef Saad; Yuanzhe Xi (CoRR, 2025)

Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages. - Michael Sun; Weize Yuan; Gang Liu; Wojciech Matusik; Jie Chen 007 (CoRR, 2025)

Directed Graph Grammars for Sequence-based Learning. - Michael Sun; Orion Foo; Gang Liu; Wojciech Matusik; Jie Chen 007 (CoRR, 2025)

Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve. - Yuanzhe Liu 001; Ryan Deng; Tim Kaler; Xuhao Chen 001; Charles E. Leiserson; Yao Ma; Jie Chen 007 (CoRR, 2025)

Decomposing the Entropy-Performance Exchange: The Missing Keys to Unlocking Effective Reinforcement Learning. - Jia Deng; Jie Chen 007; Zhipeng Chen 001; Wayne Xin Zhao; Ji-Rong Wen (CoRR, 2025)

From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR. - Jia Deng; Jie Chen 007; Zhipeng Chen 001; Daixuan Cheng; Fei Bai; Beichen Zhang; Yinqian Min; Yanzipeng Gao; Wayne Xin Zhao; Ji-Rong Wen (CoRR, 2025)