Shroff, Ness

30 publications

NeurIPS 2025 Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models Yuchen Liang, Renxiang Huang, Lifeng Lai, Ness Shroff, Yingbin Liang

ICLR 2025 Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness Shroff

NeurIPS 2025 Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees Yuchen Liang, Yingbin Liang, Lifeng Lai, Ness Shroff

ICLR 2025 How to Find the Exact Pareto Front for Multi-Objective MDPs? Yining Li, Peizhong Ju, Ness Shroff

ICML 2025 Provably Efficient RL for Linear MDPs Under Instantaneous Safety Constraints in Non-Convex Feature Spaces Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi, Fatemeh Nourzad, Eylem Ekici, Ness Shroff

ICLR 2025 Theory on Mixture-of-Experts in Continual Learning Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness Shroff

ICLR 2025 Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness Shroff

ICML 2025 Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness Shroff

ICLR 2024 Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning Peizhong Ju, Arnob Ghosh, Ness Shroff

ICLR 2024 Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping Yining Li, Peizhong Ju, Ness Shroff

AISTATS 2024 Towards Achieving Sub-Linear Regret and Hard Constraint Violation in Model-Free RL Arnob Ghosh, Xingyu Zhou, Ness Shroff

ICML 2023 A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints Ming Shi, Yingbin Liang, Ness Shroff

ICLR 2023 Achieving Sub-Linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation Arnob Ghosh, Xingyu Zhou, Ness Shroff

ICLR 2023 Near-Optimal Adversarial Reinforcement Learning with Switching Costs Ming Shi, Yingbin Liang, Ness Shroff

NeurIPS 2023 Non-Convex Bilevel Optimization with Time-Varying Objective Functions Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness Shroff

AISTATS 2023 Provably Efficient Model-Free Algorithms for Non-Stationary CMDPs Honghao Wei, Arnob Ghosh, Ness Shroff, Lei Ying, Xingyu Zhou

ICLR 2023 Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning Peizhong Ju, Yingbin Liang, Ness Shroff

ICML 2023 Theory on Forgetting and Generalization of Continual Learning Sen Lin, Peizhong Ju, Yingbin Liang, Ness Shroff

AISTATS 2022 Weighted Gaussian Process Bandits for Non-Stationary Environments Yuntian Deng, Xingyu Zhou, Baekjin Kim, Ambuj Tewari, Abhishek Gupta, Ness Shroff

NeurIPSW 2022 Conditional Moment Alignment for Improved Generalization in Federated Learning Jayanth Reddy Regatti, Songtao Lu, Abhishek Gupta, Ness Shroff

NeurIPS 2022 On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model Peizhong Ju, Xiaojun Lin, Ness Shroff

NeurIPS 2022 Provably Efficient Model-Free Constrained RL with Linear Function Approximation Arnob Ghosh, Xingyu Zhou, Ness Shroff

ICML 2021 On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models Peizhong Ju, Xiaojun Lin, Ness Shroff

NeurIPS 2021 Sample Complexity Bounds for Active Ranking from Multi-Wise Comparisons Wenbo Ren, Jia Liu, Ness Shroff

ICML 2020 The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons Wenbo Ren, Jia Liu, Ness Shroff

AISTATS 2019 Computation Efficient Coded Linear Transform Sinong Wang, Jiashang Liu, Ness Shroff, Pengyu Yang

ICML 2019 Data Poisoning Attacks on Stochastic Bandits Fang Liu, Ness Shroff

NeurIPS 2019 On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons Wenbo Ren, Jia Liu, Ness Shroff

ICML 2018 Coded Sparse Matrix Multiplication Sinong Wang, Jiashang Liu, Ness Shroff

NeurIPS 2017 A New Alternating Direction Method for Linear Programming Sinong Wang, Ness Shroff