Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
We used the YFILTER filtering system for experiments on updating profiles and setting thresholds. We developed a new method of using language models for updating profiles that is ...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A ...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish...