In this paper, we describe a compilation system that automates much of the process of performance tuning that is currently done manually by application programmers interested in h...
Nastaran Baradaran, Jacqueline Chame, Chun Chen, P...
Several recent works have used neural networks to discriminate vigilance states in humans from electroencephalographic (EEG) signals. Our study aims at being more exhaustive. It t...
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
In this paper we present a simple yet accurate model to forecast electricity load with Artificial Neural Networks (ANNs). We analyze the problem domain and choose the most adequat...
This article presents a method aiming at quantifying the visual similarity between an image and a class model. This kind of problem is recurrent in many applications such as objec...