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» Learning Weighted Automata
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129
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ECIR
2007
Springer
15 years 2 months ago
A Bayesian Approach for Learning Document Type Relevance
Retrieval accuracy can be improved by considering which document type should be filtered out and which should be ranked higher in the result list. Hence, document type can be used...
Peter C. K. Yeung, Stefan Büttcher, Charles L...
97
Voted
NIPS
2008
15 years 2 months ago
Generative and Discriminative Learning with Unknown Labeling Bias
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
Miroslav Dudík, Steven J. Phillips
99
Voted
NIPS
1994
15 years 1 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
91
Voted
ICML
2004
IEEE
16 years 1 months ago
A multiplicative up-propagation algorithm
We present a generalization of the nonnegative matrix factorization (NMF), where a multilayer generative network with nonnegative weights is used to approximate the observed nonne...
Jong-Hoon Ahn, Seungjin Choi, Jong-Hoon Oh
139
Voted
GECCO
2010
Springer
232views Optimization» more  GECCO 2010»
15 years 1 months ago
Genetic algorithms for automatic classification of moving objects
This paper presents an integrated approach, combining a state-of-the-art commercial object detection system and genetic algorithms (GA)-based learning for automatic object classif...
Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosen...