stochastic-linear-bandits

This paper proposes Absolute Thompson Sampling (ATS), a modification of Thompson Sampling that ensures optimism in expectation by using absolute exploration noise, enabling a simpler UCB-style regret analysis while maintaining computational efficiency. It achieves regret matching existing TS bounds, and introduces an ensemble variant that converges to UCB behavior.