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KDD
1995
ACM
148views Data Mining» more  KDD 1995»
13 years 11 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
ICML
2010
IEEE
13 years 6 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
NIPS
1992
13 years 8 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
CORR
2010
Springer
193views Education» more  CORR 2010»
13 years 6 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
UMUAI
2008
110views more  UMUAI 2008»
13 years 7 months ago
Modeling self-efficacy in intelligent tutoring systems: An inductive approach
Abstract. Self-efficacy is an individual's belief about her ability to perform well in a given situation. Because selfefficacious students are effective learners, endowing int...
Scott W. McQuiggan, Bradford W. Mott, James C. Les...