Priyank Agrawal

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 13

Top Topics

Multinomial Logit

Contextual Bandit

Top Venues

Publications

Priyank Agrawal, Shipra Agrawal
Optimistic Q-learning for average reward and episodic reinforcement learning. CoRR (2024)
Navdeep Kumar, Priyank Agrawal, Kfir Yehuda Levy, Shie Mannor
Policy Gradient with Tree Search (PGTS) in Reinforcement Learning Evades Local Maxima. Tiny Papers @ ICLR (2024)
Priyank Agrawal, Theja Tulabandhula, Vashist Avadhanula
A tractable online learning algorithm for the multinomial logit contextual bandit. Eur. J. Oper. Res. 310 (2) (2023)
Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. CoRR (2022)
Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. EC (2022)
Priyank Agrawal, Jinglin Chen, Nan Jiang
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. AAAI (2021)
Priyank Agrawal, Theja Tulabandhula
Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect. CoRR (2020)
Priyank Agrawal, Vashist Avadhanula, Theja Tulabandhula
Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit. CoRR (2020)
Priyank Agrawal, Theja Tulabandhula
Incentivising Exploration and Recommendations for Contextual Bandits with Payments. CoRR (2020)
Priyank Agrawal, Jinglin Chen, Nan Jiang
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. CoRR (2020)
Priyank Agrawal, Theja Tulabandhula
Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect. UAI (2020)
Priyank Agrawal, Theja Tulabandhula
Incentivising Exploration and Recommendations for Contextual Bandits with Payments. EUMAS/AT (2020)
Priyank Agrawal, Theja Tulabandhula
Bandits with Temporal Stochastic Constraints. CoRR (2018)