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ICML
2009
IEEE
15 years 10 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
KDD
2006
ACM
113views Data Mining» more  KDD 2006»
15 years 10 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
DFG
2009
Springer
15 years 4 months ago
A Survey on Approximation Algorithms for Scheduling with Machine Unavailability
In this chapter we present recent contributions in the field of sequential job scheduling on network machines which work in parallel; these are subject to temporary unavailability...
Florian Diedrich, Klaus Jansen, Ulrich M. Schwarz,...
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
14 years 11 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
AIPS
2009
14 years 10 months ago
Navigation Planning in Probabilistic Roadmaps with Uncertainty
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...
Michael Kneebone, Richard Dearden