35 search results - page 4 / 7 » Covariate-dependent dictionary learning and sparse coding |
ICPR
2010
IEEE
14 years 1 months ago
2010
IEEE
Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dict...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
CVPR
2012
IEEE
11 years 10 months ago
2012
IEEE
Top-down visual saliency facilities object localization by providing a discriminative representation of target objects and a probability map for reducing the search space. In this...
ICCV
2011
IEEE
12 years 7 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
JMLR
2010
13 years 6 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...