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» Modeling Classification and Inference Learning
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CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 9 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
JMLR
2006
120views more  JMLR 2006»
13 years 9 months ago
Kernel-Based Learning of Hierarchical Multilabel Classification Models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Juho Rousu, Craig Saunders, Sándor Szedm&aa...
TSP
2010
13 years 3 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
ICCV
2003
IEEE
14 years 11 months ago
Learning a Classification Model for Segmentation
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
Xiaofeng Ren, Jitendra Malik
IJCNN
2008
IEEE
14 years 3 months ago
Shedding weights: More with less
—Traditional connectionist classification models place an emphasis on learned synaptic weights. Based on neurobiological evidence, a new approach is developed and experimentally ...
Tsvi Achler, Cyrus Omar, Eyal Amir