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ICML
2006
IEEE
15 years 10 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
NIPS
2007
14 years 11 months ago
On higher-order perceptron algorithms
A new algorithm for on-line learning linear-threshold functions is proposed which efficiently combines second-order statistics about the data with the ”logarithmic behavior” ...
Claudio Gentile, Fabio Vitale, Cristian Brotto
ICONIP
2007
14 years 11 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor
FOCS
1999
IEEE
15 years 1 months ago
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
Rosa I. Arriaga, Santosh Vempala
GECCO
2006
Springer
157views Optimization» more  GECCO 2006»
15 years 1 months ago
gLINC: identifying composability using group perturbation
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
David Jonathan Coffin, Christopher D. Clack