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Found 4 papers, 0 papers with code
On Independent Samples Along the Langevin Diffusion and the Unadjusted Langevin Algorithm
We study the rate at which the initial and current random variables become independent along a Markov chain, focusing on the Langevin diffusion in continuous time and the Unadjusted Langevin Algorithm (ULA) in discrete time.
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
Thompson sampling (TS) is widely used in sequential decision making due to its ease of use and appealing empirical performance.
Submodular + Concave
It has been well established that first order optimization methods can converge to the maximal objective value of concave functions and provide constant factor approximation guarantees for (non-convex/non-concave) continuous submodular functions.
On Adaptivity in Information-constrained Online Learning
We then consider revealing action-partial monitoring games -- a version of label efficient prediction with additive information costs, which in general are known to lie in the \textit{hard} class of games having minimax regret of order $T^{\frac{2}{3}}$.
