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AIPS
2004
14 years 11 months ago
Learning Domain-Specific Control Knowledge from Random Walks
We describe and evaluate a system for learning domainspecific control knowledge. In particular, given a planning domain, the goal is to output a control policy that performs well ...
Alan Fern, Sung Wook Yoon, Robert Givan
ICIP
1998
IEEE
15 years 11 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
ICIP
2003
IEEE
15 years 11 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
ICRA
2002
IEEE
106views Robotics» more  ICRA 2002»
15 years 2 months ago
An Improved Random Neighborhood Graph Approach
As a general framework to determine a collision-free feedback motion strategies, the Random Neighborhood Graph (RNG) approach [19] defines a global navigation function over an ap...
Libo Yang, Steven M. LaValle
FSTTCS
1991
Springer
15 years 1 months ago
Randomizing Reductions of Search Problems
This paper closes a gap in the foundations of the theory of average case complexity. First, we clarify the notion of a feasible solution for a search problem and prove its robustne...
Andreas Blass, Yuri Gurevich