Recommender systems (RSs) are popular tools dealing with information overload problems in eCommerce Web sites. RSs match user preferences with item representations and recommend t...
Fabiana Lorenzi, Francesco Ricci, Mara Abel, Ana L...
Wiener filtering is one of the most widely used methods in audio source separation. It is often applied on time-frequency representations of signals, such as the short-time Fourier...
Jonathan Le Roux, Emmanuel Vincent, Yuu Mizuno, Hi...
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...