— We aim to perform robust and fast vision-based localization using a pre-existing large map of the scene. A key step in localization is associating the features extracted from t...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance function...
Jie Yu, Jaume Amores, Nicu Sebe, Petia Radeva, Qi ...
We present a novel approach to concept learning in which a coevolutionary genetic algorithm is applied to the construction of an immune system whose antibodies can discriminate bet...
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...