This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
This paper presents a distributed algorithm for wireless adhoc networks that runs in polylogarithmic number of rounds in the size of the network and constructs a lightweight, line...
The increasing availability of information about people's context makes it possible to deploy context-sensitive services, where access to resources provided or managed by a s...
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...