In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
Takamitsu Matsubara, Tetsuro Morimura, Jun Morimot...
We define a new reduced model to represent coloured images. We propose to use two components for a full definition of a colour instead of three. To that end we take advantage of...
Frederic Garcia, Djamila Aouada, Bruno Mirbach, Bj...
Anticipating and characterizing damages in layered carbon fiberreinforced polymers is a challenging problem. Non-destructive evaluation using ultrasonic signals is a well-establi...
Nicolas Bochud, Angel M. Gomez, Guillermo Rus, Jos...
Abstract. In this paper, we address the problem of opinion analysis using a probabilistic approach to the underlying structure of different types of opinions or sentiments around ...
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...