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97
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ICML
2010
IEEE
15 years 1 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
99
Voted
KDD
1995
ACM
139views Data Mining» more  KDD 1995»
15 years 4 months ago
Extracting Support Data for a Given Task
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Bernhard Schölkopf, Chris Burges, Vladimir Va...
121
Voted
AGI
2008
15 years 1 months ago
Transfer Learning and Intelligence: an Argument and Approach
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
Matthew E. Taylor, Gregory Kuhlmann, Peter Stone
144
Voted
ECML
2006
Springer
15 years 4 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
90
Voted
LREC
2008
104views Education» more  LREC 2008»
15 years 1 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...