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» Learning from Highly Structured Data by Decomposition
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ISBI
2011
IEEE
14 years 1 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...
ICIP
2005
IEEE
15 years 11 months ago
Non-parametric image super-resolution using multiple images
In this paper, we present a novel learning based framework for performing super-resolution using multiple images. We model the image as an undirected graphical model over image pa...
Mithun Das Gupta, ShyamSundar Rajaram, Nemanja Pet...
RECOMB
2004
Springer
15 years 10 months ago
Modeling and Analysis of Heterogeneous Regulation in Biological Networks
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Irit Gat-Viks, Amos Tanay, Ron Shamir
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
13 years 5 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
BMCBI
2011
14 years 1 months ago
The Proteogenomic Mapping Tool
Background: High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the...
William S. Sanders, Nan Wang, Susan M. Bridges, Br...