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ICPR
2008
IEEE
16 years 7 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
ICML
2002
IEEE
16 years 7 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton
STOC
2003
ACM
122views Algorithms» more  STOC 2003»
16 years 6 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
SEMWEB
2009
Springer
16 years 1 months ago
An Algorithm for Learning with Probabilistic Description Logics
Probabilistic Description Logics are the basis of ontologies in the Semantic Web. Knowledge representation and reasoning for these logics have been extensively explored in the last...
José Eduardo Ochoa Luna, Fabio Gagliardi Co...
ICALT
2005
IEEE
16 years 3 days ago
The Use of an Adaptive Hypermedia Learning System to Support a New Pedagogical Model
The purpose of this paper is to present the current state and future development of the PLATINEA project. This project allows students and teachers to create and to consolidate kn...
Constatino Martins, Isabel Azevedo, Carlos Vaz de ...