424 search results - page 63 / 85 » Boosted sampling: approximation algorithms for stochastic op... |
IWANN
1999
Springer
13 years 12 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
ICCV
2005
IEEE
14 years 1 months ago
2005
IEEE
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
ICRA
2005
IEEE
14 years 1 months ago
2005
IEEE
— In the real world, noisy sensors and limited communication make it difficult for robot teams to coordinate in tightly coupled tasks. Team members cannot simply apply single-ro...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
APPROX
2009
Springer
14 years 2 months ago
2009
Springer
Submodular-function maximization is a central problem in combinatorial optimization, generalizing many important NP-hard problems including Max Cut in digraphs, graphs and hypergr...