We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
— Exploratory activities seem to be crucial for our cognitive development. According to psychologists, exploration is an intrinsically rewarding behaviour. The developmental robo...