arXiv stat.ML
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Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set
arXiv:2607.23679v1 Announce Type: cross Abstract: Recent years have witnessed increasing interests in tackling heteroscedastic noise in bandits and reinforcement learning. In these works, the cumulative variance of the noise $Lambda = sum_{t=1}^T sigma_t^2$, where $sigma_t^2$ is the variance of the noise at round $