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» Learning from Highly Structured Data by Decomposition
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TSP
2011
197views more  TSP 2011»
14 years 4 months ago
Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
ICML
2006
IEEE
15 years 10 months ago
Spectral clustering for multi-type relational data
Clustering on multi-type relational data has attracted more and more attention in recent years due to its high impact on various important applications, such as Web mining, e-comm...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...
BMCBI
2010
189views more  BMCBI 2010»
14 years 10 months ago
High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABERTOOTH
Background: Protein alignments are an essential tool for many bioinformatics analyses. While sequence alignments are accurate for proteins of high sequence similarity, they become...
Florian Teichert, Jonas Minning, Ugo Bastolla, Mar...
ECML
2006
Springer
14 years 11 months ago
Efficient Large Scale Linear Programming Support Vector Machines
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Suvrit Sra
ICIP
2007
IEEE
15 years 11 months ago
Three Dimensional Face Recognition using Wavelet Decomposition of Range Images
Interest in face recognition systems has increased significantly due to the emergence of significant commercial opportunities in surveillance and security applications. In this pa...
Sina Jahanbin, Hyohoon Choi, Alan C. Bovik, Kennet...