Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
We describe a causal learning method, which employs measuring the strength of statistical dependences in terms of the Hilbert-Schmidt norm of kernel-based cross-covariance operato...
— Matching images with large geometric and iconic changes (e.g. faces under different poses and facial expressions) is an open research problem in computer vision. There are two ...
In this paper, several approaches for language portability of dialogue systems are investigated with a focus on the spoken language understanding (SLU) component. We show that the...
Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user’s satisfacti...