536 search results - page 84 / 108 » Residual Algorithms: Reinforcement Learning with Function Ap... |
147
Voted
CVPR
2007
IEEE
16 years 4 months ago
2007
IEEE
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
119
Voted
FOCS
2002
IEEE
15 years 7 months ago
2002
IEEE
We give the first polynomial time algorithm to learn any function of a constant number of halfspaces under the uniform distribution on the Boolean hypercube to within any constan...
149
Voted
CVPR
2008
IEEE
16 years 4 months ago
2008
IEEE
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
139
Voted
IJON
2007
15 years 2 months ago
2007
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
134
Voted
UAI
2008
15 years 4 months ago
2008
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...