1 citations · 1 across the 7 of their papers we have counts for
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Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
Anupam Nayak, Tong Yang, Osman Yagan +2
Reverse Kullback-Leibler (KL) divergence-based regularization with respect to a fixed reference policy is widely used in modern reinforcement learning to preserve the desired trait…
On Balancing Sparsity with Reliable Connectivity in Distributed Network Design with Random K-out Graphs
Mansi Sood, Eray Can Elumar, Osman Yagan
In several applications in distributed systems, an important design criterion is ensuring that the network is sparse, i.e., does not contain too many edges, while achieving reliabl…
Cost-aware LLM-based Online Dataset Annotation
Eray Can Elumar, Cem Tekin, Osman Yagan
Recent advances in large language models (LLMs) have enabled automated dataset labeling with minimal human supervision. While majority voting across multiple LLMs can improve label…
Bandits with Anytime Knapsacks
Eray Can Elumar, Cem Tekin, Osman Yagan
We consider bandits with anytime knapsacks (BwAK), a novel version of the BwK problem where there is an \textit{anytime} cost constraint instead of a total cost budget. This proble…