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CIKM
1997
Springer
13 years 11 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
ICML
1999
IEEE
14 years 7 months ago
Machine-Learning Applications of Algorithmic Randomness
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
Volodya Vovk, Alexander Gammerman, Craig Saunders
FLAIRS
2006
13 years 8 months ago
Coalition Formation Meets Information Theory
The process of coalition formation, where distinct autonomous agents come together to act as a coherent group is an important form of interaction in multiagent systems. Previous w...
Victor Palmer, Thomas R. Ioerger
ICDM
2006
IEEE
109views Data Mining» more  ICDM 2006»
14 years 1 months ago
Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory
Heterogeneous object co-clustering has become an important research topic in data mining. In early years of this research, people mainly worked on two types of heterogeneous data ...
Bin Gao, Tie-Yan Liu, Wei-Ying Ma
ISCAS
2007
IEEE
126views Hardware» more  ISCAS 2007»
14 years 1 months ago
Theory and Implementation of an Analog-to-Information Converter using Random Demodulation
— The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at subNyquist acquisition rates. We develop new theory, algorithms...
Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tam...