We propose a fast iterative classification algorithm for Kernel Fisher Discriminant (KFD) using heterogeneous kernel models. In contrast with the standard KFD that requires the us...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
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
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample. It partiti...