1419 search results - page 67 / 284 » Approximation Methods for Supervised Learning |
EDUTAINMENT
2007
Springer
14 years 4 months ago
2007
Springer
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
ICML
2001
IEEE
14 years 10 months ago
2001
IEEE
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
JMLR
2010
13 years 8 months ago
2010
Nonlinear dimensionality reduction methods are often used to visualize high-dimensional data, although the existing methods have been designed for other related tasks such as mani...
NAACL
2010
13 years 8 months ago
2010
Most learning algorithms for undirected graphical models require complete inference over at least one instance before parameter updates can be made. SampleRank is a rankbased lear...
AAMAS
2007
Springer
13 years 10 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...