3607 search results - page 68 / 722 » Learning with structured sparsity |
PKDD
1999
Springer
14 years 12 days ago
1999
Springer
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
NIPS
2000
13 years 9 months ago
2000
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
JMLR
2010
13 years 2 months ago
2010
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
AUSAI
2008
Springer
13 years 10 months ago
2008
Springer
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...