Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
We present a principled methodology for filtering news stories by formal measures of information novelty, and show how the techniques can be used to custom-tailor newsfeeds based ...
Evgeniy Gabrilovich, Susan T. Dumais, Eric Horvitz
Web image search is inspired by text search techniques; it mainly relies on indexing textual data that surround the image file. But retrieval results are often noisy and image pro...
Recognition of a protein’s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: tw...