We present a novel weighted approach for shrinkage functions learning in image denoising. The proposed approach optimizes the shape of the shrinkage functions and maximizes denois...
Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by thes...
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
In many vision problems, rotation-invariant analysis is necessary or preferred. Popular solutions are mainly based on pose normalization or brute-force learning, neglecting the in...
Kun Liu, Qing Wang, Wolfgang Driever, Olaf Ronnebe...
We study the problem of learning mixtures of distributions, a natural formalization of clustering. A mixture of distributions is a collection of distributions D = {D1, . . . DT },...