Priyank Agrawal

17 papers A* 3A 1Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Optimistic Q-learning for average reward and episodic reinforcement learning extended abstract. COLT Priyank Agrawal, Shipra Agrawal
2025	J	`jnl`	Q-learning with Posterior Sampling. CoRR Priyank Agrawal, Shipra Agrawal, Azmat Azati
2024	J	`jnl`	Improved Sample Complexity for Global Convergence of Actor-Critic Algorithms. CoRR Navdeep Kumar, Priyank Agrawal, Giorgia Ramponi, Kfir Yehuda Levy, Shie Mannor
2024	J	`jnl`	Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. Math. Oper. Res. Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
2024	J	`jnl`	Optimistic Q-learning for average reward and episodic reinforcement learning. CoRR Priyank Agrawal, Shipra Agrawal
2024	—	`conf`	Policy Gradient with Tree Search (PGTS) in Reinforcement Learning Evades Local Maxima. Tiny Papers @ ICLR Navdeep Kumar, Priyank Agrawal, Kfir Yehuda Levy, Shie Mannor
2023	J	`jnl`	A tractable online learning algorithm for the multinomial logit contextual bandit. Eur. J. Oper. Res. Priyank Agrawal, Theja Tulabandhula, Vashist Avadhanula
2022	A*	`conf`	Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. EC Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
2022	J	`jnl`	Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. CoRR Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
2021	A*	`conf`	Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. AAAI Priyank Agrawal, Jinglin Chen, Nan Jiang
2020	J	`jnl`	Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit. CoRR Priyank Agrawal, Vashist Avadhanula, Theja Tulabandhula
2020	J	`jnl`	Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. CoRR Priyank Agrawal, Jinglin Chen, Nan Jiang
2020	—	`conf`	Incentivising Exploration and Recommendations for Contextual Bandits with Payments. EUMAS/AT Priyank Agrawal, Theja Tulabandhula
2020	J	`jnl`	Incentivising Exploration and Recommendations for Contextual Bandits with Payments. CoRR Priyank Agrawal, Theja Tulabandhula
2020	A	`conf`	Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect. UAI Priyank Agrawal, Theja Tulabandhula
2020	J	`jnl`	Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect. CoRR Priyank Agrawal, Theja Tulabandhula
2018	J	`jnl`	Bandits with Temporal Stochastic Constraints. CoRR Priyank Agrawal, Theja Tulabandhula