Sciweavers

68 search results - page 10 / 14
» Feature-Discovering Approximate Value Iteration Methods
Sort
View
AIPS
2007
13 years 10 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
DAGSTUHL
2007
13 years 9 months ago
A Deeper Investigation of PageRank as a Function of the Damping Factor
PageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor α that spre...
Paolo Boldi, Massimo Santini, Sebastiano Vigna
CVPR
2000
IEEE
14 years 10 months ago
A General Method for Errors-in-Variables Problems in Computer Vision
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...
Bogdan Matei, Peter Meer
WWW
2005
ACM
14 years 8 months ago
PageRank as a function of the damping factor
PageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor that spreads...
Paolo Boldi, Massimo Santini, Sebastiano Vigna
LWA
2007
13 years 9 months ago
Parameter Learning for a Readability Checking Tool
This paper describes the application of machine learning methods to determine parameters for DeLite, a readability checking tool. DeLite pinpoints text segments that are difficul...
Tim vor der Brück, Johannes Leveling