Large marginwavelet-based dictionary for signal classification

This paper addresses the problem of automatic wavelet feature extraction for signal classication. We propose to jointly learn wavelet-based features (including scale and translation of the wavelet as well as its shape) and a decision function by casting the problem as a Multi-Kernel Learning problem. A novel active constraints algorithm is then proposed. Our method has been tested on a toy dataset and compared to classical methods with competitive results.