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» Reinforcement Learning with Hierarchies of Machines
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73
Voted
ICML
2009
IEEE
15 years 10 months ago
Discovering options from example trajectories
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...
ICML
2003
IEEE
15 years 10 months ago
Relativized Options: Choosing the Right Transformation
Relativized options combine model minimization methods and a hierarchical reinforcement learning framework to derive compact reduced representations of a related family of tasks. ...
Balaraman Ravindran, Andrew G. Barto
ICCS
1994
Springer
15 years 1 months ago
UDS: A Universal Data Structure
This paper gives a data structure (UDS) for supporting database retrieval, inference and machine learning that attempts to unify and extend previous work in relational databases, ...
Robert Levinson
ESANN
2003
14 years 11 months ago
Improving iterative repair strategies for scheduling with the SVM
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Kai Gersmann, Barbara Hammer
101
Voted
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...