Mohammad Pedramfar

20 papers A* 4Journal 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets.
CoRR
Yiyang Lu, Hareshkumar Jadav, Mohammad Pedramfar, Ranveer Singh, Vaneet Aggarwal
2026 J jnl
γ-weakly θ-up-concavity: Linearizable Non-Convex Optimization with Applications to DR-Submodular and OSS Functions.
CoRR
Mohammad Pedramfar, Vaneet Aggarwal
2025 J jnl
Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization.
CoRR
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
2025 J jnl
Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization.
Trans. Mach. Learn. Res.
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
2025 J jnl
Diffusion Tree Sampling: Scalable inference-time alignment of diffusion models.
CoRR
Vineet Jain, Kusha Sareen, Mohammad Pedramfar, Siamak Ravanbakhsh
2025 J jnl
Learning-Based Two-Tiered Online Optimization of Region-Wide Datacenter Resource Allocation.
IEEE Trans. Netw. Serv. Manag.
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Tian Lan, Zheqing Zhu, Chi Zhou, Pol Mauri Ruiz, Neeraj Kumar, Hongbo Dong, Vaneet Aggarwal
2025 J jnl
Multi-Armed Sampling Problem and the End of Exploration.
CoRR
Mohammad Pedramfar, Siamak Ravanbakhsh
2025 J jnl
Order-Optimal Projection-Free Algorithm for Adversarially Constrained Online Convex Optimization.
CoRR
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
2025 J jnl
Stochastic Submodular Bandits With Delayed Composite Anonymous Bandit Feedback.
IEEE Trans. Artif. Intell.
Mohammad Pedramfar, Vaneet Aggarwal
2024 J jnl
A Generalized Approach to Online Convex Optimization.
CoRR
Mohammad Pedramfar, Vaneet Aggarwal
2024 A* conf
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization.
NeurIPS
Mohammad Pedramfar, Vaneet Aggarwal
2024 J jnl
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization.
CoRR
Mohammad Pedramfar, Vaneet Aggarwal
2024 A* conf
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization.
ICLR
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal
2024 J jnl
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization.
CoRR
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher J. Quinn, Vaneet Aggarwal
2023 A* conf
A Unified Approach for Maximizing Continuous DR-submodular Functions.
NeurIPS
Mohammad Pedramfar, Christopher J. Quinn, Vaneet Aggarwal
2023 J jnl
A Unified Approach for Maximizing Continuous DR-submodular Functions.
CoRR
Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal
2023 A* conf
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning.
NeurIPS
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
2023 J jnl
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning.
CoRR
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
2023 J jnl
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback.
CoRR
Mohammad Pedramfar, Vaneet Aggarwal
2023 J jnl
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning.
CoRR
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