Aggarwal, Vaneet

69 publications

ICML 2025 A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal

ICML 2025 Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Yang Xu, Vaneet Aggarwal

AAAI 2025 Align-Pro: A Principled Approach to Prompt Optimization for LLM Alignment Prashant Trivedi, Souradip Chakraborty, Avinash Reddy, Vaneet Aggarwal, Amrit Singh Bedi, George K. Atia

ICLR 2025 Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher Brinton

TMLR 2025 Decentralized Projection-Free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal

AISTATS 2025 Every Call Is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini

NeurIPS 2025 Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learning Yang Xu, Washim Uddin Mondal, Vaneet Aggarwal

NeurIPS 2025 GeneFlow: Translation of Single-Cell Gene Expression to Histopathological Images via Rectified Flow Mengbo Wang, Shourya Verma, Aditya Malusare, Luopin Wang, Yiyang Lu, Vaneet Aggarwal, Mario Sola, Ananth Grama, Nadia Atallah Lanman

NeurIPS 2025 Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm Yang Xu, Swetha Ganesh, Washim Uddin Mondal, Qinbo Bai, Vaneet Aggarwal

NeurIPS 2025 On the Sample Complexity Bounds of Bilevel Reinforcement Learning Mudit Gaur, Utsav Singh, Amrit Singh Bedi, Raghu Pasupathy, Vaneet Aggarwal

UAI 2025 Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization Swetha Ganesh, Jiayu Chen, Washim Uddin Mondal, Vaneet Aggarwal

AISTATS 2025 Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal

ICML 2025 Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes Bhargav Ganguly, Yang Xu, Vaneet Aggarwal

NeurIPS 2025 Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach Swetha Ganesh, Vaneet Aggarwal

NeurIPS 2025 Uniform Wrappers: Bridging Concave to Quadratizable Functions in Online Optimization Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal

IJCAI 2025 Variational Offline Multi-Agent Skill Discovery Jiayu Chen, Tian Lan, Vaneet Aggarwal

ICML 2024 Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic Under Markovian Sampling with Neural Network Parametrization Mudit Gaur, Amrit Bedi, Di Wang, Vaneet Aggarwal

AAAI 2024 Combinatorial Stochastic-Greedy Bandit Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, Vaneet Aggarwal

TMLR 2024 Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal

ICML 2024 Federated Combinatorial Multi-Agent Multi-Armed Bandits Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal

NeurIPS 2024 From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-Stationary DR-Submodular Optimization Mohammad Pedramfar, Vaneet Aggarwal

TMLR 2024 Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal

NeurIPS 2024 Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints Guanyu Nie, Vaneet Aggarwal, Christopher John Quinn

ICLR 2024 Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang

AISTATS 2024 Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes Washim U. Mondal, Vaneet Aggarwal

NeurIPS 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

JMLR 2024 Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL) Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri

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

NeurIPS 2024 Sample-Efficient Constrained Reinforcement Learning with General Parameterization Washim Uddin Mondal, Vaneet Aggarwal

ICML 2024 Stochastic Q-Learning for Large Discrete Action Spaces Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini

ICML 2024 Towards Global Optimality for Practical Average Reward Reinforcement Learning Without Mixing Time Oracles Bhrij Patel, Wesley A Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Dinesh Manocha, Amrit Bedi

ICLR 2024 Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal

ICML 2023 A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback Guanyu Nie, Yididiya Y. Nadew, Yanhui Zhu, Vaneet Aggarwal, Christopher John Quinn

NeurIPS 2023 A Unified Algorithm Framework for Unsupervised Discovery of Skills Based on Determinantal Point Process Jiayu Chen, Vaneet Aggarwal, Tian Lan

NeurIPS 2023 A Unified Approach for Maximizing Continuous DR-Submodular Functions Mohammad Pedramfar, Christopher Quinn, Vaneet Aggarwal

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

ICCV 2023 Domain Adaptive Few-Shot Open-Set Learning Debabrata Pal, Deeptej More, Sai Bhargav, Dipesh Tamboli, Vaneet Aggarwal, Biplab Banerjee

NeurIPSW 2023 Double Policy Estimation for Importance Sampling in Sequence Modeling-Based Reinforcement Learning Hanhan Zhou, Tian Lan, Vaneet Aggarwal

NeurIPS 2023 Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal

NeurIPS 2023 Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-Based Gradient Updates Guangchen Lan, Han Wang, James Anderson, Christopher Brinton, Vaneet Aggarwal

TMLR 2023 Mean-Field Control Based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-Decomposable Shared Global State Washim Uddin Mondal, Vaneet Aggarwal, Satish Ukkusuri

ICML 2023 Multi-Task Hierarchical Adversarial Inverse Reinforcement Learning Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal

ICML 2023 On the Global Convergence of Fitted Q-Iteration with Two-Layer Neural Network Parametrization Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal

JMLR 2023 Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints Qinbo Bai, Vaneet Aggarwal, Ather Gattami

AISTATS 2023 Randomized Greedy Learning for Non-Monotone Stochastic Submodular Maximization Under Full-Bandit Feedback Fares Fourati, Vaneet Aggarwal, Christopher Quinn, Mohamed-Slim Alouini

JMLR 2023 Reinforcement Learning for Joint Optimization of Multiple Rewards Mridul Agarwal, Vaneet Aggarwal

TMLR 2023 Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward Washim Uddin Mondal, Vaneet Aggarwal

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

UAI 2022 An Explore-Then-Commit Algorithm for Submodular Maximization Under Full-Bandit Feedback Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn

UAI 2022 Can Mean Field Control (mfc) Approximate Cooperative Multi Agent Reinforcement Learning (marl) with Non-Uniform Interaction? Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri

TMLR 2022 Concave Utility Reinforcement Learning with Zero-Constraint Violations Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal

ICML 2022 FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning Anis Elgabli, Chaouki Ben Issaid, Amrit Singh Bedi, Ketan Rajawat, Mehdi Bennis, Vaneet Aggarwal

UAI 2022 Information Theoretic Approach to Detect Collusion in Multi-Agent Games Trevor Bonjour, Vaneet Aggarwal, Bharat Bhargava

JAIR 2022 Joint Optimization of Concave Scalarized Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal

JMLR 2022 Multi-Agent Multi-Armed Bandits with Limited Communication Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli

JMLR 2022 On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) Using Mean Field Control (MFC) Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, Satish V. Ukkusuri

TMLR 2022 On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning Washim Uddin Mondal, Vaneet Aggarwal, Satish Ukkusuri

NeurIPS 2022 PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning Hanhan Zhou, Tian Lan, Vaneet Aggarwal

UAI 2022 Regret Guarantees for Model-Based Reinforcement Learning with Long-Term Average Constraints Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal

NeurIPS 2022 Scalable Multi-Agent Covering Option Discovery Based on Kronecker Graphs Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal

AISTATS 2021 Reinforcement Learning for Constrained Markov Decision Processes Ather Gattami, Qinbo Bai, Vaneet Aggarwal

ECML-PKDD 2021 CMIX: Deep Multi-Agent Reinforcement Learning with Peak and Average Constraints Chenyi Liu, Nan Geng, Vaneet Aggarwal, Tian Lan, Yuan Yang, Mingwei Xu

UAI 2021 Communication Efficient Parallel Reinforcement Learning Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal

AAAI 2021 DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits Mridul Agarwal, Vaneet Aggarwal, Abhishek Kumar Umrawal, Christopher J. Quinn

ALT 2021 Stochastic Top-$k$ Subset Bandits with Linear Space and Non-Linear Feedback Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal

L4DC 2020 Efficient Large-Scale Gaussian Process Bandits by Believing Only Informative Actions Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel

JMLR 2020 GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis, Vaneet Aggarwal

ICCV 2017 Efficient Low Rank Tensor Ring Completion Wenqi Wang, Vaneet Aggarwal, Shuchin Aeron

JMLR 2017 Rank Determination for Low-Rank Data Completion Morteza Ashraphijuo, Xiaodong Wang, Vaneet Aggarwal