Kevin Jamieson

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20232026

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stat.ML2026

Batched Stochastic Linear Bandits with 1-Bit Communication Constraints

Ivan Lau, Daniel McMorrow, Kevin Jamieson +1

We study stochastic linear bandits under a natural combination of batching and communication constraints: the time horizon is partitioned into batches of equal size $B$ , and during…

stat.ML2026

On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits

Leo Maynard-Zhang, Zhihan Xiong, Kevin Jamieson +1

We study the fixed-budget best-arm identification (BAI) problem in non-stationary linear bandits. Concretely, given a fixed time budget $T \in N$ , finite arm set $\mathcal{…

stat.ML2026

Efficient Uncoupled Learning Dynamics with $O ~ (T^{- 1/4})$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback

Arnab Maiti, Claire Jie Zhang, Kevin Jamieson +3

In this paper, we study last-iterate convergence of learning algorithms in bilinear saddle-point problems, a preferable notion of convergence that captures the day-to-day behavior…

Batched Stochastic Linear Bandits with 1-Bit Communication Constraints

On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits

Efficient Uncoupled Learning Dynamics with O~(T−1/4) Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback

Efficient Uncoupled Learning Dynamics with $O ~ (T^{- 1/4})$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback