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ICASSP
2011
IEEE
14 years 10 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
ACL
2011
14 years 10 months ago
Jointly Learning to Extract and Compress
We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose fea...
Taylor Berg-Kirkpatrick, Dan Gillick, Dan Klein
CVPR
2009
IEEE
17 years 1 months ago
Learning query-dependent prefilters for scalable image retrieval
We describe an algorithm for similar-image search which is designed to be efficient for extremely large collections of images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
CVPR
2003
IEEE
16 years 8 months ago
Learning Appearance and Transparency Manifolds of Occluded Objects in Layers
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Brendan J. Frey, Nebojsa Jojic, Anitha Kannan
CVPR
2008
IEEE
16 years 8 months ago
The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling
Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...