Mohammad Pedramfar

According to our database, Mohammad Pedramfar authored at least 12 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Stochastic Submodular Bandits With Delayed Composite Anonymous Bandit Feedback.

Mohammad Pedramfar, Vaneet Aggarwal

IEEE Trans. Artif. Intell., July, 2025

Multi-Armed Sampling Problem and the End of Exploration.

Mohammad Pedramfar, Siamak Ravanbakhsh

CoRR, July, 2025

Diffusion Tree Sampling: Scalable inference-time alignment of diffusion models.

Vineet Jain, Kusha Sareen, Mohammad Pedramfar, Siamak Ravanbakhsh

CoRR, June, 2025

Learning-Based Two-Tiered Online Optimization of Region-Wide Datacenter Resource Allocation.

Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Tian Lan, Zheqing Zhu, Chi Zhou, Pol Mauri Ruiz, Neeraj Kumar, Hongbo Dong, Vaneet Aggarwal

IEEE Trans. Netw. Serv. Manag., February, 2025

Order-Optimal Projection-Free Algorithm for Adversarially Constrained Online Convex Optimization.

Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal

CoRR, February, 2025

Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization.

Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal

CoRR, January, 2025

2024

A Generalized Approach to Online Convex Optimization.

Mohammad Pedramfar, Vaneet Aggarwal

CoRR, 2024

From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization.

Mohammad Pedramfar, Vaneet Aggarwal

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization.

Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning.

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

CoRR, 2023

A Unified Approach for Maximizing Continuous DR-submodular Functions.

Mohammad Pedramfar, Christopher J. Quinn, Vaneet Aggarwal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning.

Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023