65 search results - page 6 / 13 » Gradient Descent for General Reinforcement Learning |
ML
2002
ACM
14 years 9 months ago
2002
ACM
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
CORR
2010
Springer
14 years 9 months ago
2010
Springer
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
CVPR
2012
IEEE
13 years 5 days ago
2012
IEEE
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
NIPS
2008
14 years 11 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
NIPS
2008
14 years 11 months ago
2008
Many motor skills in humanoid robotics can be learned using parametrized motor primitives as done in imitation learning. However, most interesting motor learning problems are high...