995 search results - page 6 / 199 » Learning Useful Horn Approximations |
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
This paper addresses an innovative approach to informed enhancement of damaged sound. It uses sparse approximations with a learned dictionary of atoms modeling the main components...
JMLR
2006
13 years 7 months ago
2006
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
NIPS
2007
13 years 8 months ago
2007
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
AAMAS
2007
Springer
13 years 7 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...