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116
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ICML
2002
IEEE
16 years 4 months ago
Learning to Share Distributed Probabilistic Beliefs
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Christopher Leckie, Kotagiri Ramamohanarao
136
Voted
ICML
1998
IEEE
16 years 4 months ago
An Information-Theoretic Definition of Similarity
Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an in...
Dekang Lin
135
Voted
ICMLA
2008
15 years 5 months ago
Target Selection: A New Learning Paradigm and Its Application to Genetic Association Studies
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
100
Voted
COLT
2004
Springer
15 years 9 months ago
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
Constantine Caramanis, Shie Mannor
151
Voted
ICMLA
2009
15 years 1 months ago
ECON: A Kernel Basis Pursuit Algorithm with Automatic Feature Parameter Tuning, and its Application to Photometric Solids Approx
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...