We discuss the problem of finding a good state representation in stochastic systems with observations. We develop a duality theory that generalizes existing work in predictive sta...
Christopher Hundt, Prakash Panangaden, Joelle Pine...
We present and relate recent results in prediction based on countable classes of either probability (semi-)distributions or base predictors. Learning by Bayes, MDL, and stochastic ...
Performance Engineering is concerned with the reliable prediction and estimation of the performance of scientific and engineering applications on a variety of parallel and distrib...
We present a general method for explaining individual predictions of classification models. The method is based on fundamental concepts from coalitional game theory and prediction...
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...