Wang, Mengdi

134 publications

TMLR 2026 A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Huan-ang Gao, Jiayi Geng, Wenyue Hua, Mengkang Hu, Xinzhe Juan, Hongzhang Liu, Shilong Liu, Jiahao Qiu, Xuan Qi, Qihan Ren, Yiran Wu, Hongru Wang, Han Xiao, Yuhang Zhou, Shaokun Zhang, Jiayi Zhang, Jinyu Xiang, Yixiong Fang, Qiwen Zhao, Dongrui Liu, Cheng Qian, Zhenhailong Wang, Minda Hu, Huazheng Wang, Qingyun Wu, Heng Ji, Mengdi Wang

ICLR 2025 A Common Pitfall of Margin-Based Language Model Alignment: Gradient Entanglement Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi

ICML 2025 A First-Order Generative Bilevel Optimization Framework for Diffusion Models Quan Xiao, Hui Yuan, A F M Saif, Gaowen Liu, Ramana Rao Kompella, Mengdi Wang, Tianyi Chen

ICML 2025 BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation Lian Liu, Xiandong Zhao, Guanchen Li, Dong Li, Mengdi Wang, Yinhe Han, Xiaowei Li, Ying Wang

NeurIPS 2025 Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning Yinjie Wang, Ling Yang, Ye Tian, Ke Shen, Mengdi Wang

ICLR 2025 Collab: Controlled Decoding Using Mixture of Agents for LLM Alignment Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh

NeurIPS 2025 DISC: Dynamic Decomposition Improves LLM Inference Scaling Jonathan Light, Wei Cheng, Benjamin Riviere, Yue Wu, Masafumi Oyamada, Mengdi Wang, Yisong Yue, Santiago Paternain, Haifeng Chen

ICLRW 2025 DISC: Dynamic Decomposition Improves LLM Inference Scaling Jonathan Light, Wei Cheng, Yue Wu, Masafumi Oyamada, Mengdi Wang, Santiago Paternain, Haifeng Chen

IJCAI 2025 Deep Reinforcement Learning for Efficient and Fair Allocation of Healthcare Resources Yikuan Li, Chengsheng Mao, Kaixuan Huang, Hanyin Wang, Zheng Yu, Mengdi Wang, Yuan Luo

ICLR 2025 Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data Hengyu Fu, Zehao Dou, Jiawei Guo, Mengdi Wang, Minshuo Chen

NeurIPS 2025 Does Thinking More Always Help? Mirage of Test-Time Scaling in Reasoning Models Soumya Suvra Ghosal, Souradip Chakraborty, Avinash Reddy, Yifu Lu, Mengdi Wang, Dinesh Manocha, Furong Huang, Mohammad Ghavamzadeh, Amrit Singh Bedi

ICML 2025 Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models Yukang Yang, Declan Iain Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor Whittington Webb

CVPR 2025 Immune: Improving Safety Against Jailbreaks in Multi-Modal LLMs via Inference-Time Alignment Soumya Suvra Ghosal, Souradip Chakraborty, Vaibhav Singh, Tianrui Guan, Mengdi Wang, Ahmad Beirami, Furong Huang, Alvaro Velasquez, Dinesh Manocha, Amrit Singh Bedi

ICLR 2025 IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation Xinchen Zhang, Ling Yang, Guohao Li, YaQi Cai, Xie Jiake, Yong Tang, Yujiu Yang, Mengdi Wang, Bin Cui

ICLRW 2025 MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

ICML 2025 MATH-Perturb: Benchmarking LLMs’ Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

NeurIPS 2025 MMaDA: Multimodal Large Diffusion Language Models Ling Yang, Ye Tian, Bowen Li, Xinchen Zhang, Ke Shen, Yunhai Tong, Mengdi Wang

ICLRW 2025 NoWag: A Unified Framework for Shape Preserving Compression of Large Language Models Lawrence Ray Liu, Inesh Chakrabarti, Yixiao Li, Mengdi Wang, Tuo Zhao, Lin Yang

ICCV 2025 Preacher: Paper-to-Video Agentic System Jingwei Liu, Ling Yang, Hao Luo, Fan Wang, Hongyan Li, Mengdi Wang

NeurIPS 2025 ReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought Reasoning in LLMs Jiaru Zou, Ling Yang, Jingwen Gu, Jiahao Qiu, Ke Shen, Jingrui He, Mengdi Wang

ICLR 2025 Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow Fu-Yun Wang, Ling Yang, Zhaoyang Huang, Mengdi Wang, Hongsheng Li

NeurIPS 2025 Securing the Language of Life: Inheritable Watermarks from DNA Language Models to Proteins Zaixi Zhang, Ruofan Jin, Le Cong, Mengdi Wang

ICLRW 2025 Temporal Consistency for LLM Reasoning Process Error Identification Jiacheng Guo, Yue Wu, Jiahao Qiu, Kaixuan Huang, Xinzhe Juan, Ling Yang, Mengdi Wang

ICLR 2025 Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias Rui Lu, Runzhe Wang, Kaifeng Lyu, Xitai Jiang, Gao Huang, Mengdi Wang

NeurIPS 2025 Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models Yingqing Guo, Yukang Yang, Hui Yuan, Mengdi Wang

IJCAI 2025 WenyanGPT: A Large Language Model for Classical Chinese Tasks Xinyu Yao, Mengdi Wang, Bo Chen, Xiaobing Zhao

NeurIPSW 2024 A Common Pitfall of Margin-Based Language Model Alignment: Gradient Entanglement Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi

NeurIPS 2024 A Theoretical Perspective for Speculative Decoding Algorithm Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

TMLR 2024 Adversarial Attacks on Online Learning to Rank with Stochastic Click Models Zichen Wang, Rishab Balasubramanian, Hui Yuan, Chenyu Song, Mengdi Wang, Huazheng Wang

ICML 2024 Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson

ICLRW 2024 Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson

NeurIPSW 2024 Embodied LLM Agents Learn to Cooperate in Organized Teams Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang

NeurIPS 2024 Fast Best-of-N Decoding via Speculative Rejection Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette

NeurIPS 2024 FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling Zaixi Zhang, Mengdi Wang, Qi Liu

NeurIPS 2024 Global Convergence in Training Large-Scale Transformers Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan

NeurIPS 2024 Gradient Guidance for Diffusion Models: An Optimization Perspective Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang

ICML 2024 Information-Directed Pessimism for Offline Reinforcement Learning Alec Koppel, Sujay Bhatt, Jiacheng Guo, Joe Eappen, Mengdi Wang, Sumitra Ganesh

ICML 2024 Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? a Theoretical Perspective Lei Zhao, Mengdi Wang, Yu Bai

NeurIPSW 2024 Latent Diffusion Models for Controllable RNA Sequence Generation Kaixuan Huang, Yukang Yang, Kaidi Fu, Yanyi Chu, Le Cong, Mengdi Wang

ICML 2024 MaxMin-RLHF: Alignment with Diverse Human Preferences Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha, Furong Huang, Amrit Bedi, Mengdi Wang

ICMLW 2024 MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Furong Huang, Dinesh Manocha, Amrit Bedi, Mengdi Wang

NeurIPS 2024 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

NeurIPS 2024 Offline Multitask Representation Learning for Reinforcement Learning Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

JMLR 2024 On the Sample Complexity and Metastability of Heavy-Tailed Policy Search in Continuous Control Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel

NeurIPS 2024 One-Layer Transformer Provably Learns One-Nearest Neighbor in Context Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang

ICLR 2024 PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback Souradip Chakraborty, Amrit Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang

AISTATS 2024 Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang

ICMLW 2024 SAIL: Self-Improving Efficient Online Alignment of Large Language Models Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit Bedi, Furong Huang

JMLR 2024 Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICLR 2024 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

ICMLW 2024 SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths Kaixuan Huang, Xudong Guo, Mengdi Wang

ICML 2024 Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei

ICML 2024 Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang

NeurIPS 2024 Transfer Q-Star : Principled Decoding for LLM Alignment Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang

AAAI 2024 Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization Jiahao Qiu, Hui Yuan, Jinghong Zhang, Wentao Chen, Huazheng Wang, Mengdi Wang

AAAI 2024 TurboSVM-FL: Boosting Federated Learning Through SVM Aggregation for Lazy Clients Mengdi Wang, Anna Bodonhelyi, Efe Bozkir, Enkelejda Kasneci

AAAI 2024 Visual Adversarial Examples Jailbreak Aligned Large Language Models Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal

AISTATS 2023 Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu

ICLR 2023 Deep Reinforcement Learning for Cost-Effective Medical Diagnosis Zheng Yu, Yikuan Li, Joseph Chahn Kim, Kaixuan Huang, Yuan Luo, Mengdi Wang

JMLR 2023 Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang

ICML 2023 Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

NeurIPS 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

ICMLW 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

JMLR 2023 Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition Chengzhuo Ni, Yaqi Duan, Munther Dahleh, Mengdi Wang, Anru R. Zhang

ICLR 2023 Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang

NeurIPSW 2023 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

ICLR 2023 Offline Reinforcement Learning with Differentiable Function Approximation Is Provably Efficient Ming Yin, Mengdi Wang, Yu-Xiang Wang

NeurIPS 2023 Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma

ICMLW 2023 Principal-Driven Reward Design and Agent Policy Alignment via Bilevel-RL Souradip Chakraborty, Amrit Bedi, Alec Koppel, Furong Huang, Mengdi Wang

NeurIPSW 2023 Protein Language Models Enable Accurate Cryptic Ligand Binding Pocket Prediction David A Bloore, Joseph Chahn Kim, Karan Kapoor, Eric Chen, Kaifu Gao, Mengdi Wang, Ming-Hong Hao

COLT 2023 Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang

ICML 2023 Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang

ICMLW 2023 Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Zihao Li, Zhuoran Yang, Mengdi Wang

ICLR 2023 Representation Learning for Low-Rank General-Sum Markov Games Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Zihan Ding, Chi Jin, Mengdi Wang

NeurIPS 2023 Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang

ICML 2023 STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty, Amrit Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha

ICLR 2023 Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds Using Deep Networks Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICMLW 2023 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

NeurIPSW 2023 Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules Joseph Chahn Kim, David A Bloore, Karan Kapoor, Jun Feng, Ming-Hong Hao, Mengdi Wang

ICMLW 2023 Scaling In-Context Demonstrations with Structured Attention Tianle Cai, Kaixuan Huang, Jason D. Lee, Mengdi Wang

ICML 2023 Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang

NeurIPSW 2023 Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization Jiahao Qiu, Hui Yuan, Jinghong Zhang, Wentao Chen, Huazheng Wang, Mengdi Wang

NeurIPS 2023 Unified Off-Policy Learning to Rank: A Reinforcement Learning Perspective Zeyu Zhang, Yi Su, Hui Yuan, Yiran Wu, Rishab Balasubramanian, Qingyun Wu, Huazheng Wang, Mengdi Wang

ICMLW 2023 Visual Adversarial Examples Jailbreak Aligned Large Language Models Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Mengdi Wang, Prateek Mittal

NeurIPS 2022 Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvari, Mengdi Wang

NeurIPS 2022 Communication Efficient Distributed Learning for Kernelized Contextual Bandits Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang

NeurIPS 2022 Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks Shuoguang Yang, Xuezhou Zhang, Mengdi Wang

ICML 2022 Efficient Reinforcement Learning in Block MDPs: A Model-Free Representation Learning Approach Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun

AAAI 2022 Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel

ICLR 2022 Near-Optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang

ICML 2022 Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang

UAI 2022 Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang

ICML 2022 Optimal Estimation of Policy Gradient via Double Fitted Iteration Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang

IJCAI 2022 Parameter-Efficient Sparsity for Large Language Models Fine-Tuning Yuchao Li, Fuli Luo, Chuanqi Tan, Mengdi Wang, Songfang Huang, Shen Li, Junjie Bai

NeurIPSW 2022 Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal, Yuda Song, Kaiwen Wang, Mengdi Wang, Wen Sun, Xuezhou Zhang

ICLRW 2022 Teamwork Reinforcement Learning with Concave Utilities Zheng Yu, Junyu Zhang, Zheng Wen, Andrea Tacchetti, Mengdi Wang, Ian Gemp

AISTATS 2021 Generalization Bounds for Stochastic Saddle Point Problems Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang

AISTATS 2021 Online Sparse Reinforcement Learning Botao Hao, Tor Lattimore, Csaba Szepesvari, Mengdi Wang

ICML 2021 Bootstrapping Fitted Q-Evaluation for Off-Policy Inference Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvari, Mengdi Wang

NeurIPS 2021 On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method Junyu Zhang, Chengzhuo Ni, Zheng Yu, Csaba Szepesvari, Mengdi Wang

ICML 2021 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang

CVPR 2021 Towards Compact CNNs via Collaborative Compression Yuchao Li, Shaohui Lin, Jianzhuang Liu, Qixiang Ye, Mengdi Wang, Fei Chao, Fan Yang, Jincheng Ma, Qi Tian, Rongrong Ji

L4DC 2020 A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes Hao Gong, Mengdi Wang

NeurIPS 2020 Generalized Leverage Score Sampling for Neural Networks Jason Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu

NeurIPS 2020 High-Dimensional Sparse Linear Bandits Botao Hao, Tor Lattimore, Mengdi Wang

ICML 2020 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation Yaqi Duan, Zeyu Jia, Mengdi Wang

ICML 2020 Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin Yang

L4DC 2020 Model-Based Reinforcement Learning with Value-Targeted Regression Zeyu Jia, Lin Yang, Csaba Szepesvari, Mengdi Wang

NeurIPS 2020 Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan

ICML 2020 Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin Yang, Mengdi Wang

AISTATS 2020 Sketching Transformed Matrices with Applications to Natural Language Processing Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang

AISTATS 2020 Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye

NeurIPS 2020 Variational Policy Gradient Method for Reinforcement Learning with General Utilities Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvari, Mengdi Wang

JMLR 2019 Approximation Hardness for a Class of Sparse Optimization Problems Yichen Chen, Yinyu Ye, Mengdi Wang

ICMLW 2019 Crowdsourcing Reinforcement Learning to Optimize Knee Replacement Pathway Hao Lu, Mengdi Wang

NeurIPS 2019 Learning Low-Dimensional State Embeddings and Metastable Clusters from Time Series Data Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang

UAI 2019 Online Factorization and Partition of Complex Networks by Random Walk Lin Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang

MLOSS 2019 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

ICML 2019 Sample-Optimal Parametric Q-Learning Using Linearly Additive Features Lin Yang, Mengdi Wang

NeurIPS 2019 State Aggregation Learning from Markov Transition Data Yaqi Duan, Tracy Ke, Mengdi Wang

NeurIPS 2018 Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao

CVPRW 2018 Efficient Deep Learning Inference Based on Model Compression Qing Zhang, Mengru Zhang, Mengdi Wang, Wanchen Sui, Chen Meng, Jun Yang, Weidan Kong, Xiaoyuan Cui, Wei Lin

ICML 2018 Estimation of Markov Chain via Rank-Constrained Likelihood Xudong Li, Mengdi Wang, Anru Zhang

AISTATS 2018 Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu

NeurIPS 2018 Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye

ICML 2018 Scalable Bilinear Pi Learning Using State and Action Features Yichen Chen, Lihong Li, Mengdi Wang

JMLR 2017 Accelerating Stochastic Composition Optimization Mengdi Wang, Ji Liu, Ethan X. Fang

NeurIPS 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang

AISTATS 2017 Finite-Sum Composition Optimization via Variance Reduced Gradient Descent Xiangru Lian, Mengdi Wang, Ji Liu

ICML 2017 Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions Yichen Chen, Dongdong Ge, Mengdi Wang, Zizhuo Wang, Yinyu Ye, Hao Yin

NeurIPS 2016 Accelerating Stochastic Composition Optimization Mengdi Wang, Ji Liu, Ethan Fang