Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
A comparative study of parallel metaheuristics executed in grid environments is proposed, having as case study a genetic algorithm, a simulated annealing algorithm and a random se...
Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
In this paper we investigate effective versions of Hausdorff dimension which have been recently introduced by Lutz. We focus on dimension in the class E of sets computable in line...
Klaus Ambos-Spies, Wolfgang Merkle, Jan Reimann, F...
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...