Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Background: The omics fields promise to revolutionize our understanding of biology and biomedicine. However, their potential is compromised by the challenge to analyze the huge da...
This is the second part of a two-part paper on optimal design of limited feedback single-user and multiuser spatial multiplexing systems. The first part of the paper studies the si...
Consider the following seemingly rhetorical question: Is it crucial for a property-tester to know the error parameter in advance? Previous papers dealing with various testing prob...
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has running ...