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ICCV
2003
IEEE
16 years 5 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann
ICML
2006
IEEE
16 years 4 months ago
Learning high-order MRF priors of color images
In this paper, we use large neighborhood Markov random fields to learn rich prior models of color images. Our approach extends the monochromatic Fields of Experts model (Roth &...
Alex J. Smola, Julian John McAuley, Matthias O. Fr...
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ICML
2004
IEEE
16 years 4 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ICML
2003
IEEE
16 years 4 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
ICML
1998
IEEE
16 years 4 months ago
Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus
Cross-language latent semantic indexing is a method that learns useful languageindependent vector representations of terms through a statistical analysis of a documentaligned text...
Michael L. Littman, Fan Jiang, Greg A. Keim