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» The Complexity of the Matching-Cut Problem
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ICML
2001
IEEE
16 years 8 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICML
1998
IEEE
16 years 8 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
ISBI
2002
IEEE
16 years 7 months ago
Deformable registration of DT-MRI data based on transformation invariant tensor characteristics
Conventional deformable registration methods are mostly driven by the interface between different brain structures. In recent years, Diffusion Tensor Magnetic Resonance Imaging (D...
Alexandre Guimond, Charles R. G. Guttmann, Simon K...
KDD
2008
ACM
146views Data Mining» more  KDD 2008»
16 years 7 months ago
Constraint programming for itemset mining
The relationship between constraint-based mining and constraint programming is explored by showing how the typical constraints used in pattern mining can be formulated for use in ...
Luc De Raedt, Tias Guns, Siegfried Nijssen
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 7 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
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