A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This paper explores minimax-Bayes solutions for reinforcement learning problems.
Bayesian methods suffer from the problem of how to specify prior beliefs. One interesting idea is to consider worst-case priors. This requires solving a stochastic zero-sum game. In this paper, we extend well-known results from bandit theory in order to discover minimax-Bayes policies and discuss when they are practica…
Study optimizes best-arm identification with minimax and Bayes strategies.
Optimal adaptive experiment for choosing best treatment with binary outcomes.