We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
This is a survey of some theoretical results on boosting obtained from an analogous treatment of some regression and classi cation boosting algorithms. Some related papers include...