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» Learning aspect models with partially labeled data
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ICCV
2007
IEEE
14 years 9 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven
ICML
2004
IEEE
14 years 8 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
ICCV
2003
IEEE
14 years 9 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
ICASSP
2008
IEEE
14 years 1 months ago
Music preference learning with partial information
We consider the problem of online learning in a changing environment under sparse user feedback. Specifically, we address the classification of music types according to a user...
Yvonne Moh, Peter Orbanz, Joachim M. Buhmann
ICML
2010
IEEE
13 years 5 months ago
Approximate Predictive Representations of Partially Observable Systems
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Monica Dinculescu, Doina Precup