Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative...
Thomas L. Griffiths, Mark Steyvers, David M. Blei,...
We introduce the aggregating cache, and demonstrate how it can be used to reduce the number of file retrieval requests made by a caching client, improving storage system performan...
Two neural networks that are trained on their mutual output synchronize to an identical time dependant weight vector. This novel phenomenon can be used for creation of a secure cr...
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...