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COLT
2005
Springer
14 years 1 months ago
Generalization Error Bounds Using Unlabeled Data
We present two new methods for obtaining generalization error bounds in a semi-supervised setting. Both methods are based on approximating the disagreement probability of pairs of ...
Matti Kääriäinen
IJCAI
2007
13 years 9 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
BMCBI
2006
169views more  BMCBI 2006»
13 years 7 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
IJCAI
2007
13 years 9 months ago
Learning Implied Global Constraints
Finding a constraint network that will be efficiently solved by a constraint solver requires a strong expertise in Constraint Programming. Hence, there is an increasing interest i...
Christian Bessière, Remi Coletta, Thierry P...
ILP
2005
Springer
14 years 1 months ago
Generalization Behaviour of Alkemic Decision Trees
Abstract. This paper is concerned with generalization issues for a decision tree learner for structured data called Alkemy. Motivated by error bounds established in statistical lea...
Kee Siong Ng