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...
This paper presents new methods for restructuring logic networks based on fast Boolean techniques. The basis for these are 1) a cut based view of a logic network, 2) exploiting th...
Alan Mishchenko, Robert K. Brayton, Satrajit Chatt...
In this paper, we proposed an improved “bottom-up” variable-size block matching method. Different from previous work, the proposed method does not need any threshold during th...
Abstract. Feature selection has improved the performance of text clustering. In this paper, a local feature selection technique is incorporated in the dynamic hierarchical compact ...
We propose a novel general framework with a boosting algorithm to achieve active object classification by view selection. The proposed framework actively decides the next best vie...