Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
In this paper, we develop a general model, called Latency-Rate servers (LR servers), for the analysis of traffic scheduling algorithms in broadband packet networks. The behavior of...
We prove the strongest known bound for the risk of hypotheses selected from the ensemble generated by running a learning algorithm incrementally on the training data. Our result i...
Algorithms and Programming Languages is a core subject in the BS Degree in Mathematics at the authors’ university. Some of the students are very interested in computer programmi...