Mohammad Pedramfar

Publication Activity (10 Years)

Years Active: 2023-2024
Publications (10 Years): 10

Top Topics

Multi Armed Bandits

Diminishing Returns

Reinforcement Learning

Top Venues

Publications

Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization. ICLR (2024)
Mohammad Pedramfar, Vaneet Aggarwal
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization. CoRR (2024)
Mohammad Pedramfar, Vaneet Aggarwal
A Generalized Approach to Online Convex Optimization. CoRR (2024)
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher J. Quinn, Vaneet Aggarwal
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization. CoRR (2024)
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning. CoRR (2023)
Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal
A Unified Approach for Maximizing Continuous DR-submodular Functions. CoRR (2023)
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, Hongbo Dong
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning. CoRR (2023)
Mohammad Pedramfar, Vaneet Aggarwal
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback. CoRR (2023)
Mohammad Pedramfar, Christopher J. Quinn, Vaneet Aggarwal
A Unified Approach for Maximizing Continuous DR-submodular Functions. NeurIPS (2023)
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning. NeurIPS (2023)