An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Modern functional languages offer several attractive features to support development of reliable and secure software. However, in our efforts to use Haskell for systems programmin...
Abstract—In this paper, we consider the problem of multifunctional compression with side information. The problem is how we can compress a source X so that the receiver is able t...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...