1351 search results - page 30 / 271 » Learning from compressed observations |
ICASSP
2009
IEEE
15 years 4 months ago
2009
IEEE
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
ECCV
2008
Springer
15 years 11 months ago
2008
Springer
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
IJDAR
2007
14 years 9 months ago
2007
Language usage over computer mediated discourses, like chats, emails and SMS texts, significantly differs from the standard form of the language. An urge towards shorter message l...
JMLR
2010
14 years 4 months ago
2010
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...