Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
A configuration with heterogeneous sensors using different measurement approaches most likely overcome the problem of correlated measurement errors as they occur when employing a ...
Abstract. Mutual Information (MI) is a long studied measure of coding efficiency, and many attempts to apply it to population coding have been made. However, this is a computationa...
d Abstract] Robert Krauthgamer James R. Lee We present a simple deterministic data structure for maintaining a set S of points in a general metric space, while supporting proximit...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...