In the paper, a new evolutionary algorithm (EA) for mixed tree learning is proposed. In non-terminal nodes of a mixed decision tree different types of tests can be placed, ranging ...
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...
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...
We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
Abstract. Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful lear...
Markus Weimer, Alexandros Karatzoglou, Alex J. Smo...