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» The Measurable Space of Stochastic Processes
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JAIR
2010
131views more  JAIR 2010»
13 years 8 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
COR
2010
146views more  COR 2010»
13 years 10 months ago
A search space "cartography" for guiding graph coloring heuristics
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
GECCO
2011
Springer
261views Optimization» more  GECCO 2011»
13 years 1 months ago
Spacing memetic algorithms
We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space dista...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
ICASSP
2009
IEEE
14 years 4 months ago
Instantaneous pose estimation using rotation vectors
An algorithm for estimating the pose, i.e., translation and rotation, of an extended target object is introduced. Compared to conventional methods, where pose estimation is perfor...
Frederik Beutler, Marco F. Huber, Uwe D. Hanebeck
MCS
2002
Springer
13 years 9 months ago
A Discussion on the Classifier Projection Space for Classifier Combining
In classifier combining, one tries to fuse the information that is given by a set of base classifiers. In such a process, one of the difficulties is how to deal with the variabilit...
Elzbieta Pekalska, Robert P. W. Duin, Marina Skuri...