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111
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JMLR
2010
159views more  JMLR 2010»
14 years 9 months ago
Semi-Supervised Learning with Max-Margin Graph Cuts
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...
135
Voted
IDEAL
2007
Springer
15 years 8 months ago
Analysis of Tiling Microarray Data by Learning Vector Quantization and Relevance Learning
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. T...
Michael Biehl, Rainer Breitling, Yang Li
122
Voted
ENTCS
2008
114views more  ENTCS 2008»
15 years 2 months ago
Term-graph Rewriting in Tom Using Relative Positions
In this paper, we present the implementation in Tom of a de Bruijn indices generalization allowing the representation of term-graphs over an algebraic signature. By adding pattern...
Emilie Balland, Paul Brauner
119
Voted
COMBINATORICS
1998
76views more  COMBINATORICS 1998»
15 years 2 months ago
An Exploration of the Permanent-Determinant Method
The permanent-determinant method and its generalization, the HafnianPfaffian method, are methods to enumerate perfect matchings of plane graphs that were discovered by P. W. Kaste...
Greg Kuperberg
148
Voted
ICCV
2007
IEEE
16 years 4 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...