← Authors

Vaneet Aggarwal

55 papers · 2017–2026 · 12 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (8) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (6) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 Keyword Pioneer 🌍 Conference Polyglot (12) πŸŒ‰ Interdisciplinary Bridge πŸ† Grand Slam πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (172) ❓ The Questioner ⚑ Prolific Year (14) πŸš€ Conference Pioneer πŸ’Ž Century Club (54) πŸ”₯ Unstoppable (6)

Conferences

ICML (11) NIPS (10) AAAI (7) JMLR (7) UAI (6) AISTATS (5) ICLR (3) ICCV (2) ALT (1) CVPR (1) IJCAI (1) L4DC (1)

Top co-authors

Mridul Agarwal (10) Washim Uddin Mondal (9) Qinbo Bai (7) Mohamed-Slim Alouini (6) Fares Fourati (6) Amrit Singh Bedi (5) Christopher John Quinn (5) Jiayu Chen (5) Tian Lan (5) Mohammad Pedramfar (4)

Keywords

regret bound (14) natural policy gradient (7) constrained markov decision process (7) sample complexity (7) reinforcement learning (6) multi-armed bandit (6) multi-agent reinforcement learning (6) markov decision process (6) stochastic optimization (4) communication efficiency (4) submodular maximization (4) constraint violation (4) multi-agent system (3) alternating direction method of multiplier (3) combinatorial bandit (3) policy gradient (3) skill discovery (2) model compression (2) primal-dual algorithm (2) distributed learning (2)

Papers

ECPv2: Fast, Efficient, and Scalable Global Optimization of Lipschitz Functions AAAI 2026
Align-Pro: A Principled Approach to Prompt Optimization for LLM Alignment AAAI 2025
Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach ICML 2025
Variational Offline Multi-agent Skill Discovery IJCAI 2025
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs AISTATS 2025
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants AISTATS 2025
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes ICML 2025
A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach ICML 2025
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis ICLR 2025
Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization UAI 2025
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes AAAI 2024
Combinatorial Stochastic-Greedy Bandit AAAI 2024
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes AISTATS 2024
Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints NIPS 2024
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles ICML 2024
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization ICLR 2024
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model ICLR 2024
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization ICML 2024
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization NIPS 2024
Sample-Efficient Constrained Reinforcement Learning with General Parameterization NIPS 2024
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm NIPS 2024
Stochastic Q-learning for Large Discrete Action Spaces ICML 2024
Federated Combinatorial Multi-Agent Multi-Armed Bandits ICML 2024
Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL) JMLR 2024
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm AAAI 2023
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning NIPS 2023
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates NIPS 2023
A Unified Approach for Maximizing Continuous DR-submodular Functions NIPS 2023
A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process NIPS 2023
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback AISTATS 2023
Domain Adaptive Few-Shot Open-Set Learning ICCV 2023
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning ICML 2023
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization ICML 2023
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback ICML 2023
Reinforcement Learning for Joint Optimization of Multiple Rewards JMLR 2023
Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints JMLR 2023
An explore-then-commit algorithm for submodular maximization under full-bandit feedback UAI 2022
Multi-Agent Multi-Armed Bandits with Limited Communication JMLR 2022
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs NIPS 2022
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach AAAI 2022
Regret guarantees for model-based reinforcement learning with long-term average constraints UAI 2022
Information theoretic approach to detect collusion in multi-agent games UAI 2022
Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction? UAI 2022
PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning NIPS 2022
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning ICML 2022
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC) JMLR 2022
Stochastic Top-$K$ Subset Bandits with Linear Space and Non-Linear Feedback ALT 2021
Reinforcement Learning for Constrained Markov Decision Processes AISTATS 2021
Communication efficient parallel reinforcement learning UAI 2021
DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits AAAI 2021
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning JMLR 2020
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions L4DC 2020
Wide Compression: Tensor Ring Nets CVPR 2018
Rank Determination for Low-Rank Data Completion JMLR 2017
Efficient Low Rank Tensor Ring Completion ICCV 2017