Escaping Saddle Points for Zeroth-order Nonconvex Optimization using Estimated Gradient Descent. - Qinbo Bai; Mridul Agarwal; Vaneet Aggarwal (CoRR, 2019)

Escaping Saddle Points for Zeroth-order Non-convex Optimization using Estimated Gradient Descent. - Qinbo Bai; Mridul Agarwal; Vaneet Aggarwal (CISS, 2020)

Model-Free Algorithm and Regret Analysis for MDPs with Peak Constraints. - Qinbo Bai; Ather Gattami; Vaneet Aggarwal (CoRR, 2020)

Deep Learning-Based Channel Estimation Algorithm Over Time Selective Fading Channels. - Qinbo Bai; Jintao Wang 001; Yue Zhang 011; Jian Song 004 (IEEE Trans. Cogn. Commun. Netw., 2020)

Reinforcement Learning for Constrained Markov Decision Processes. - Ather Gattami; Qinbo Bai; Vaneet Aggarwal (AISTATS, 2021)

Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm. - Qinbo Bai; Mridul Agarwal; Vaneet Aggarwal (CoRR, 2021)

Markov Decision Processes with Long-Term Average Constraints. - Mridul Agarwal; Qinbo Bai; Vaneet Aggarwal (CoRR, 2021)

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. - Qinbo Bai; Amrit Singh Bedi; Mridul Agarwal; Alec Koppel; Vaneet Aggarwal (AAAI, 2022)

Regret guarantees for model-based reinforcement learning with long-term average constraints. - Mridul Agarwal; Qinbo Bai; Vaneet Aggarwal (UAI, 2022)

Joint Optimization of Concave Scalarized Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm. - Qinbo Bai; Mridul Agarwal; Vaneet Aggarwal (J. Artif. Intell. Res., 2022)

Concave Utility Reinforcement Learning with Zero-Constraint Violations. - Mridul Agarwal; Qinbo Bai; Vaneet Aggarwal (Trans. Mach. Learn. Res., 2022)

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. - Qinbo Bai; Amrit Singh Bedi; Vaneet Aggarwal (AAAI, 2023)

Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints. - Qinbo Bai; Vaneet Aggarwal; Ather Gattami (J. Mach. Learn. Res., 2023)

A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints. - Nan Geng; Qinbo Bai; Chenyi Liu; Tian Lan 001; Vaneet Aggarwal; Yuan Yang 001; Mingwei Xu (IEEE Trans. Veh. Technol., 2023)

Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes. - Qinbo Bai; Washim Uddin Mondal; Vaneet Aggarwal (AAAI, 2024)

Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm. - Qinbo Bai; Washim Uddin Mondal; Vaneet Aggarwal (NeurIPS, 2024)

Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms. - Vaneet Aggarwal; Washim Uddin Mondal; Qinbo Bai (Found. Trends Optim., 2024)

Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm. - Yang Xu 003; Swetha Ganesh; Washim Uddin Mondal; Qinbo Bai; Vaneet Aggarwal (CoRR, 2025)