137 search results - page 14 / 28 » Sparse Semi-supervised Learning Using Conjugate Functions |
UAI
2003
13 years 9 months ago
2003
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
ICML
2009
IEEE
14 years 2 months ago
2009
IEEE
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...