Pedramfar, Mohammad

7 publications

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

NeurIPS 2025 Diffusion Tree Sampling: Scalable Inference‑time Alignment of Diffusion Models Vineet Jain, Kusha Sareen, Mohammad Pedramfar, Siamak Ravanbakhsh

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

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

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

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