In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
To deal with the issue of data unbalanced condition among a task of multilingual speech recognition and a phenomenon of pronunciation variations across languages, we propose an ap...
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
This paper addresses two closely related aspects of subjective information. First, no two agents necessarily see the same thing when they observe the same object. Second, no two a...