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TSP
2010
13 years 2 months ago
Covariance estimation in decomposable Gaussian graphical models
Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
Ami Wiesel, Yonina C. Eldar, Alfred O. Hero
ETVC
2008
13 years 9 months ago
Sparse Multiscale Patches for Image Processing
Abstract. This paper presents a framework to define an objective measure of the similarity (or dissimilarity) between two images for image processing. The problem is twofold: 1) de...
Paolo Piro, Sandrine Anthoine, Eric Debreuve, Mich...
ICCV
2005
IEEE
14 years 10 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
BMCBI
2006
149views more  BMCBI 2006»
13 years 8 months ago
Identification of biomarkers from mass spectrometry data using a "common" peak approach
Background: Proteomic data obtained from mass spectrometry have attracted great interest for the detection of early-stage cancer. However, as mass spectrometry data are high-dimen...
Tadayoshi Fushiki, Hironori Fujisawa, Shinto Eguch...
CVPR
2005
IEEE
14 years 10 months ago
Corrected Laplacians: Closer Cuts and Segmentation with Shape Priors
We optimize over the set of corrected laplacians (CL) associated with a weighted graph to improve the average case normalized cut (NCut) of a graph. Unlike edge-relaxation SDPs, o...
David Tolliver, Gary L. Miller, Robert T. Collins