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ICML
2001
IEEE
14 years 10 months ago
An Improved Predictive Accuracy Bound for Averaging Classifiers
We present an improved bound on the difference between training and test errors for voting classifiers. This improved averaging bound provides a theoretical justification for popu...
John Langford, Matthias Seeger, Nimrod Megiddo
ECAI
2006
Springer
14 years 1 months ago
Patch Learning for Incremental Classifier Design
We present a learning algorithm for nominal data. It builds a classifier by adding iteratively a simple patch function that modifies the current classifier. Its main advantage lies...
Rudy Sicard, Thierry Artières, Eric Petit
IJCAI
2007
13 years 11 months ago
Deictic Option Schemas
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
ATAL
2010
Springer
13 years 10 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko
ICASSP
2008
IEEE
14 years 4 months ago
Generalized Gaussian Markov random field image restoration using variational distribution approximation
In this paper we propose novel algorithms for image restoration and parameter estimation with a Generalized Gaussian Markov Random Field prior utilizing variational distribution a...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...