We propose a multiple source domain adaptation method, referred to as Domain Adaptation Machine (DAM), to learn a robust decision function (referred to as target classifier) for l...
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
We propose a new low complexity and fast converging frequencydomain adaptive algorithm for sparse system identification. This is achieved by exploiting the MMax and SP tap-select...
Andy W. H. Khong, Xiang Lin, Milos Doroslovacki, P...
Abstract. Learning in complex contexts often requires pure induction to be supported by various kinds of meta-information. Providing such information is a critical, difficult and ...
Stefano Ferilli, Floriana Esposito, Teresa Maria A...
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...