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TSP
2010
14 years 4 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 ...
91
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ICCV
2007
IEEE
15 years 11 months ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic
ICCV
2005
IEEE
15 years 11 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
94
Voted
ICIP
2010
IEEE
14 years 7 months ago
Combining free energy score spaces with information theoretic kernels: Application to scene classification
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Manuele Bicego, Alessandro Perina, Vittorio Murino...
ICCV
2005
IEEE
15 years 3 months ago
Learning Non-Generative Grammatical Models for Document Analysis
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
Michael Shilman, Percy Liang, Paul A. Viola