The standard so-called experts algorithms are methods for utilizing a given set of “experts” to make good choices in a sequential decision-making problem. In the standard setti...
This paper explores online learning approaches for detecting malicious Web sites (those involved in criminal scams) using lexical and host-based features of the associated URLs. W...
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffr...
We study the problem of online learning of multiple tasks in parallel. On each online round, the algorithm receives an instance and makes a prediction for each one of the parallel ...
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...