Jie Chen - RankMe

129 papers A* 23A 2C 1Misc 3Journal 88Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing? CoRR Guoxin Chen, Fanzhe Meng, Jiale Zhao, Minghao Li, Daixuan Cheng, Huatong Song, Jie Chen, Yuzhi Lin, Hui Chen, Xin Zhao, Ruihua Song, Chang Liu, Cheng Chen, Kai Jia, Ji-Rong Wen
2026	J	`jnl`	Immersion in the GitHub Universe: Scaling Coding Agents to Mastery. CoRR Jiale Zhao, Guoxin Chen, Fanzhe Meng, Minghao Li, Jie Chen, Hui Xu, Yongshuai Sun, Xin Zhao, Ruihua Song, Yuan Zhang, Peng Wang, Cheng Chen, Jirong Wen, Kai Jia
2025	J	`jnl`	An Empirical Study on Eliciting and Improving R1-like Reasoning Models. CoRR Zhipeng Chen, Yingqian Min, Beichen Zhang, Jie Chen, Jinhao Jiang, Daixuan Cheng, Wayne Xin Zhao, Zheng Liu, Xu Miao, Yang Lu, Lei Fang, Zhongyuan Wang, Ji-Rong Wen
2025	J	`jnl`	Decomposing the Entropy-Performance Exchange: The Missing Keys to Unlocking Effective Reinforcement Learning. CoRR Jia Deng, Jie Chen, Zhipeng Chen, Wayne Xin Zhao, Ji-Rong Wen
2025	A*	`conf`	Directed Graph Grammars for Sequence-based Learning. ICML Michael Sun, Orion Foo, Gang Liu, Wojciech Matusik, Jie Chen
2025	J	`jnl`	Directed Graph Grammars for Sequence-based Learning. CoRR Michael Sun, Orion Foo, Gang Liu, Wojciech Matusik, Jie Chen
2025	A*	`conf`	Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages. ICML Michael Sun, Weize Yuan, Gang Liu, Wojciech Matusik, Jie Chen
2025	J	`jnl`	Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages. CoRR Michael Sun, Weize Yuan, Gang Liu, Wojciech Matusik, Jie Chen
2025	J	`jnl`	From Trial-and-Error to Improvement: A Systematic Analysis of LLM Exploration Mechanisms in RLVR. CoRR Jia Deng, Jie Chen, Zhipeng Chen, Daixuan Cheng, Fei Bai, Beichen Zhang, Yinqian Min, Yanzipeng Gao, Wayne Xin Zhao, Ji-Rong Wen
2025	J	`jnl`	GPTOpt: Towards Efficient LLM-Based Black-Box Optimization. CoRR Jamison Meindl, Yunsheng Tian, Tony Cui, Veronika Thost, Zhang-Wei Hong, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2025	J	`jnl`	Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve. CoRR Yuanzhe Liu, Ryan Deng, Tim Kaler, Xuhao Chen, Charles E. Leiserson, Yao Ma, Jie Chen
2025	J	`jnl`	Mixed Precision Orthogonalization-Free Projection Methods for Eigenvalue and Singular Value Problems. CoRR Tianshi Xu, Zechen Zhang, Jie Chen, Yousef Saad, Yuanzhe Xi
2025	A*	`conf`	Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning. ICLR Gang Liu, Michael Sun, Wojciech Matusik, Meng Jiang, Jie Chen
2025	J	`jnl`	Neighborhood Sampling Does Not Learn the Same Graph Neural Network. CoRR Zehao Niu, Mihai Anitescu, Jie Chen
2025	A*	`conf`	Procedural Synthesis of Synthesizable Molecules. ICLR Michael Sun, Alston Lo, Minghao Guo, Jie Chen, Connor W. Coley, Wojciech Matusik
2025	J	`jnl`	R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning. CoRR Huatong Song, Jinhao Jiang, Yingqian Min, Jie Chen, Zhipeng Chen, Wayne Xin Zhao, Lei Fang, Ji-Rong Wen
2025	A*	`conf`	Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework. EMNLP Jie Chen, Jinhao Jiang, Yingqian Min, Zican Dong, Shijie Wang, Wayne Xin Zhao, Ji-Rong Wen
2025	J	`jnl`	Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework. CoRR Jie Chen, Jinhao Jiang, Yingqian Min, Zican Dong, Shijie Wang, Wayne Xin Zhao, Ji-Rong Wen
2025	—	`conf`	Towards Effective and Efficient Continual Pre-training of Large Language Models. ACL (1) Jie Chen, Zhipeng Chen, Jiapeng Wang, Kun Zhou, Yutao Zhu, Jinhao Jiang, Yingqian Min, 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
2025	—	`conf`	YuLan-Mini: Pushing the Limits of Open Data-efficient Language Model. ACL (1) Yiwen Hu, Huatong Song, Jie Chen, Jia Deng, Jiapeng Wang, Kun Zhou, Yutao Zhu, Jinhao Jiang, Zican Dong, Yang Lu, Xu Miao, Xin Zhao, Ji-Rong Wen
2025	J	`jnl`	ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization. CoRR Jamison Meindl, Yunsheng Tian, Tony Cui, Veronika Thost, Zhang-Wei Hong, Johannes Dürholt, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	A*	`conf`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. ICML Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	J	`jnl`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. CoRR Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	J	`jnl`	GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. Trans. Mach. Learn. Res. Xinwei Zhang, Mingyi Hong, Jie Chen
2024	—	`conf`	Identifying Money Laundering Subgraphs on the Blockchain. ICAIF Kiwhan Song, Mohamed Ali Dhraief, Muhua Xu, Locke Cai, Xuhao Chen, Arvind Mithal, Jie Chen
2024	J	`jnl`	Identifying Money Laundering Subgraphs on the Blockchain. CoRR Kiwhan Song, Mohamed Ali Dhraief, Muhua Xu, Locke Cai, Xuhao Chen, Arvind, Jie Chen
2024	J	`jnl`	Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems. CoRR Yingqian Min, Zhipeng Chen, Jinhao Jiang, Jie Chen, Jia Deng, Yiwen Hu, Yiru Tang, Jiapeng Wang, Xiaoxue Cheng, Huatong Song, Wayne Xin Zhao, Zheng Liu, Zhongyuan Wang, Ji-Rong Wen
2024	—	`conf`	LLMBox: A Comprehensive Library for Large Language Models. ACL (3) 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, Ranchi Zhao, Luran Ding, Yuhao Wang, Zican Dong, Chunxuan Xia, Junyi Li, Kun Zhou, Xin Zhao, Ji-Rong Wen
2024	J	`jnl`	LLMBox: A Comprehensive Library for Large Language Models. CoRR 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
2024	J	`jnl`	Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning. CoRR Gang Liu, Michael Sun, Wojciech Matusik, Meng Jiang, Jie Chen
2024	A*	`conf`	Representing Molecules as Random Walks Over Interpretable Grammars. ICML 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
2024	J	`jnl`	Representing Molecules as Random Walks Over Interpretable Grammars. CoRR 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
2024	J	`jnl`	Syntax-Guided Procedural Synthesis of Molecules. CoRR Michael Sun, Alston Lo, Wenhao Gao, Minghao Guo, Veronika Thost, Jie Chen, Connor W. Coley, Wojciech Matusik
2024	J	`jnl`	Technical Report: Enhancing LLM Reasoning with Reward-guided Tree Search. CoRR Jinhao Jiang, Zhipeng Chen, Yingqian Min, Jie Chen, Xiaoxue Cheng, Jiapeng Wang, Yiru Tang, Haoxiang Sun, Jia Deng, Wayne Xin Zhao, Zheng Liu, Dong Yan, Jian Xie, Zhongyuan Wang, Ji-Rong Wen
2024	—	`conf`	The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. ACL (1) Junyi Li, Jie Chen, Ruiyang Ren, Xiaoxue Cheng, Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
2024	J	`jnl`	The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. CoRR Junyi Li, Jie Chen, Ruiyang Ren, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
2024	J	`jnl`	The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset. CoRR Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen
2024	J	`jnl`	Towards Effective and Efficient Continual Pre-training of Large Language Models. CoRR 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
2024	—	`conf`	Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models. EMNLP (Findings) Jie Chen, Yupeng Zhang, Bingning Wang, Xin Zhao, Ji-Rong Wen, Weipeng Chen
2024	J	`jnl`	Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models. CoRR Jie Chen, Yupeng Zhang, Bingning Wang, Wayne Xin Zhao, Ji-Rong Wen, Weipeng Chen
2024	J	`jnl`	YuLan-Mini: An Open Data-efficient Language Model. CoRR Yiwen Hu, Huatong Song, Jia Deng, Jiapeng Wang, Jie Chen, Kun Zhou, Yutao Zhu, Jinhao Jiang, Zican Dong, Wayne Xin Zhao, Ji-Rong Wen
2023	J	`jnl`	A Decentralized Primal-Dual Framework for Non-Convex Smooth Consensus Optimization. IEEE Trans. Signal Process. Gabriel Mancino-Ball, Yangyang Xu, Jie Chen
2023	J	`jnl`	Bridging mean-field games and normalizing flows with trajectory regularization. J. Comput. Phys. Han Huang, Jiajia Yu, Jie Chen, Rongjie Lai
2023	—	`conf`	Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. MLSys Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2023	J	`jnl`	Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. CoRR Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2023	J	`jnl`	Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs. CoRR Tengfei Ma, Trong Nghia Hoang, Jie Chen
2023	A	`conf`	Federated learning of models pre-trained on different features with consensus graphs. UAI Tengfei Ma, Trong Nghia Hoang, Jie Chen
2023	J	`jnl`	GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. CoRR Xinwei Zhang, Mingyi Hong, Jie Chen
2023	J	`jnl`	GUAP: Graph Universal Attack Through Adversarial Patching. CoRR Xiao Zang, Jie Chen, Bo Yuan
2023	A*	`conf`	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning. ICLR Zehao Niu, Mihai Anitescu, Jie Chen
2023	J	`jnl`	Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning. CoRR Zehao Niu, Mihai Anitescu, Jie Chen
2023	A*	`conf`	Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. ICML Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
2023	J	`jnl`	Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. CoRR Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
2023	J	`jnl`	Parallel and distributed asynchronous adaptive stochastic gradient methods. Math. Program. Comput. Yangyang Xu, Yibo Xu, Yonggui Yan, Colin Sutcher-Shepard, Leopold Grinberg, Jie Chen
2023	A*	`conf`	Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization. AAAI Gabriel Mancino-Ball, Shengnan Miao, Yangyang Xu, Jie Chen
2022	—	`conf`	Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. MLSys Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2022	A*	`conf`	Data-Efficient Graph Grammar Learning for Molecular Generation. ICLR Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
2022	J	`jnl`	Data-Efficient Graph Grammar Learning for Molecular Generation. CoRR Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
2022	J	`jnl`	Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems. SIAM J. Imaging Sci. Yangyang Xu, Yibo Xu, Yonggui Yan, Jie Chen
2021	J	`jnl`	Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. CoRR Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2021	—	`conf`	CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. NeurIPS Datasets and Benchmarks 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
2021	A*	`conf`	Directed Acyclic Graph Neural Networks. ICLR Veronika Thost, Jie Chen
2021	J	`jnl`	Directed Acyclic Graph Neural Networks. CoRR Veronika Thost, Jie Chen
2021	A*	`conf`	Discrete Graph Structure Learning for Forecasting Multiple Time Series. ICLR Chao Shang, Jie Chen, Jinbo Bi
2021	J	`jnl`	Discrete Graph Structure Learning for Forecasting Multiple Time Series. CoRR Chao Shang, Jie Chen, Jinbo Bi
2021	J	`jnl`	Distributed stochastic inertial methods with delayed derivatives. CoRR Yangyang Xu, Yibo Xu, Yonggui Yan, Jie Chen
2021	J	`jnl`	Generating a Doppelganger Graph: Resembling but Distinct. CoRR Yuliang Ji, Ru Huang, Jie Chen, Yuanzhe Xi
2021	A*	`conf`	Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models. IJCAI Xiao Zang, Yi Xie, Jie Chen, Bo Yuan
2021	J	`jnl`	Graph coarsening: From scientific computing to machine learning. CoRR Jie Chen, Yousef Saad, Zechen Zhang
2021	J	`jnl`	Noise Injection-based Regularization for Point Cloud Processing. CoRR Xiao Zang, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
2021	—	`conf`	PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. APOCS Tim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja, Georgios Kollias
2021	J	`jnl`	Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. CoRR 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
2021	A*	`conf`	Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. AAAI Tengfei Ma, Jie Chen
2020	J	`jnl`	Asynchronous parallel adaptive stochastic gradient methods. CoRR Yangyang Xu, Colin Sutcher-Shepard, Yibo Xu, Jie Chen
2020	A*	`conf`	CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator. AAAI Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
2020	A*	`conf`	Embedding Compression with Isotropic Iterative Quantization. AAAI Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
2020	J	`jnl`	Embedding Compression with Isotropic Iterative Quantization. CoRR Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
2020	A*	`conf`	EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. AAAI Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B. Schardl, Charles E. Leiserson
2020	J	`jnl`	Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models. CoRR Xiao Zang, Yi Xie, Jie Chen, Bo Yuan
2020	A*	`conf`	Online Planner Selection with Graph Neural Networks and Adaptive Scheduling. AAAI Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen, Michael Katz
2019	A*	`conf`	A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019	J	`jnl`	A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019	J	`jnl`	Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. CoRR Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele, Claudio Bellei, Tom Robinson, Charles E. Leiserson
2019	J	`jnl`	CAG: A Real-time Low-cost Enhanced-robustness High-transferability Content-aware Adversarial Attack Generator. CoRR Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan
2019	J	`jnl`	Chart Auto-Encoders for Manifold Structured Data. CoRR Stefan C. Schonsheck, Jie Chen, Rongjie Lai
2019	A*	`conf`	DAG-GNN: DAG Structure Learning with Graph Neural Networks. ICML Yue Yu, Jie Chen, Tian Gao, Mo Yu
2019	J	`jnl`	DAG-GNN: DAG Structure Learning with Graph Neural Networks. CoRR Yue Yu, Jie Chen, Tian Gao, Mo Yu
2019	J	`jnl`	EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. CoRR Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson
2019	—	`conf`	Graph Enhanced Cross-Domain Text-to-SQL Generation. TextGraphs@EMNLP Siyu Huo, Tengfei Ma, Jie Chen, Maria Chang, Lingfei Wu, Michael Witbrock
2019	J	`jnl`	IPC: A Benchmark Data Set for Learning with Graph-Structured Data. CoRR Patrick Ferber, Tengfei Ma, Siyu Huo, Jie Chen, Michael Katz
2019	J	`jnl`	Relaxation-Based Coarsening for Multilevel Hypergraph Partitioning. Multiscale Model. Simul. Ruslan Shaydulin, Jie Chen, Ilya Safro
2019	J	`jnl`	Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. CoRR Tengfei Ma, Jie Chen
2018	J	`jnl`	A posteriori error estimate for computing tr(f(A)) by using the Lanczos method. Numer. Linear Algebra Appl. Jie Chen, Yousef Saad
2018	J	`jnl`	Adaptive Planner Scheduling with Graph Neural Networks. CoRR Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen, Michael Katz
2018	A*	`conf`	Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. NeurIPS Tengfei Ma, Jie Chen, Cao Xiao
2018	J	`jnl`	Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. CoRR Tengfei Ma, Jie Chen, Cao Xiao
2018	—	`conf`	FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. ICLR (Poster) Jie Chen, Tengfei Ma, Cao Xiao
2018	J	`jnl`	FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. CoRR Jie Chen, Tengfei Ma, Cao Xiao
2018	J	`jnl`	Learning low-complexity autoregressive models via proximal alternating minimization. Syst. Control. Lett. Fu Lin, Jie Chen
2018	J	`jnl`	Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. CoRR Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan
2018	J	`jnl`	Scalable Graph Learning for Anti-Money Laundering: A First Look. CoRR Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl
2018	J	`jnl`	Stochastic Gradient Descent with Biased but Consistent Gradient Estimators. CoRR Jie Chen, Ronny Luss
2017	J	`jnl`	Fast Estimation of tr(f(A)) via Stochastic Lanczos Quadrature. SIAM J. Matrix Anal. Appl. Shashanka Ubaru, Jie Chen, Yousef Saad
2017	J	`jnl`	Hierarchically Compositional Kernels for Scalable Nonparametric Learning. J. Mach. Learn. Res. Jie Chen, Haim Avron, Vikas Sindhwani
2017	C	`conf`	Learning low-complexity autoregressive models with limited time sequence data. ACC Fu Lin, Jie Chen
2017	J	`jnl`	Relaxation-Based Coarsening for Multilevel Hypergraph Partitioning. CoRR Ruslan Shaydulin, Jie Chen, Ilya Safro
2016	J	`jnl`	Analysis and Practical Use of Flexible BiCGStab. J. Sci. Comput. Jie Chen, Lois C. McInnes, Hong Zhang
2016	Misc	`conf`	Efficient one-vs-one kernel ridge regression for speech recognition. ICASSP Jie Chen, Lingfei Wu, Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran
2016	J	`jnl`	Hierarchically Compositional Kernels for Scalable Nonparametric Learning. CoRR Jie Chen, Haim Avron, Vikas Sindhwani
2016	J	`jnl`	How Accurately Should I Compute Implicit Matrix-Vector Products When Applying the Hutchinson Trace Estimator? SIAM J. Sci. Comput. Jie Chen
2016	J	`jnl`	On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps. CoRR Jie Chen, Dehua Cheng, Yan Liu
2016	A*	`conf`	Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. KDD Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan
2014	J	`jnl`	A Fast Summation Tree Code for Matérn Kernel. SIAM J. Sci. Comput. Jie Chen, Lei Wang, Mihai Anitescu
2014	J	`jnl`	A parallel linear solver for multilevel Toeplitz systems with possibly several right-hand sides. Parallel Comput. Jie Chen, Tom L. H. Li, Mihai Anitescu
2013	J	`jnl`	On the Use of Discrete Laplace Operator for Preconditioning Kernel Matrices. SIAM J. Sci. Comput. Jie Chen
2013	Misc	`conf`	Parallelizing the Conjugate Gradient Algorithm for Multilevel Toeplitz Systems. ICCS Jie Chen, Tom L. H. Li
2012	J	`jnl`	A Matrix-free Approach for Solving the Parametric Gaussian Process Maximum Likelihood Problem. SIAM J. Sci. Comput. Mihai Anitescu, Jie Chen, Lei Wang
2012	J	`jnl`	Dense Subgraph Extraction with Application to Community Detection. IEEE Trans. Knowl. Data Eng. Jie Chen, Yousef Saad
2012	J	`jnl`	Difference Filter Preconditioning for Large Covariance Matrices. SIAM J. Matrix Anal. Appl. Michael L. Stein, Jie Chen, Mihai Anitescu
2011	Misc	`conf`	A measure of the local connectivity between graph vertices. ICCS Jie Chen, Ilya Safro
2011	J	`jnl`	Algebraic Distance on Graphs. SIAM J. Sci. Comput. Jie Chen, Ilya Safro
2011	J	`jnl`	Computing f(A)b via Least Squares Polynomial Approximations. SIAM J. Sci. Comput. Jie Chen, Mihai Anitescu, Yousef Saad
2011	J	`jnl`	Trace optimization and eigenproblems in dimension reduction methods. Numer. Linear Algebra Appl. Effrosini Kokiopoulou, Jie Chen, Yousef Saad
2009	J	`jnl`	A Measure of the Connection Strengths between Graph Vertices with Applications CoRR Jie Chen, Ilya Safro
2009	A	`conf`	Divide and Conquer Strategies for Effective Information Retrieval. SDM Jie Chen, Yousef Saad
2009	J	`jnl`	Fast Approximate J. Mach. Learn. Res. Jie Chen, Haw-ren Fang, Yousef Saad
2009	J	`jnl`	Lanczos Vectors versus Singular Vectors for Effective Dimension Reduction. IEEE Trans. Knowl. Data Eng. Jie Chen, Yousef Saad
2008	J	`jnl`	Architectural Modeling from Sparsely Scanned Range Data. Int. J. Comput. Vis. Jie Chen, Baoquan Chen
2008	J	`jnl`	On the Tensor SVD and the Optimal Low Rank Orthogonal Approximation of Tensors. SIAM J. Matrix Anal. Appl. Jie Chen, Yousef Saad