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SIAMIS
2011
14 years 7 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
115
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ICML
2009
IEEE
16 years 1 months ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin
NIPS
2000
15 years 2 months ago
On Reversing Jensen's Inequality
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Tony Jebara, Alex Pentland
90
Voted
IJCV
2006
116views more  IJCV 2006»
15 years 20 days ago
Structure-Texture Image Decomposition - Modeling, Algorithms, and Parameter Selection
This paper explores various aspects of the image decomposition problem using modern variational techniques. We aim at splitting an original image f into two components u and v, whe...
Jean-François Aujol, Guy Gilboa, Tony F. Ch...
99
Voted
CADE
2007
Springer
16 years 1 months ago
Hyper Tableaux with Equality
Abstract. In most theorem proving applications, a proper treatment of equational theories or equality is mandatory. In this paper we show how to integrate a modern treatment of equ...
Björn Pelzer, Peter Baumgartner, Ulrich Furba...