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» Learning to learn with the informative vector machine
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RECOMB
2010
Springer
15 years 6 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
ICMLC
2010
Springer
15 years 2 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu
ICIP
2008
IEEE
16 years 6 months ago
Recovering wavelet relations using SVM for image denoising
Here we propose an alternative non-explicit way to take into account the relations among wavelet coefficients in natural images for denoising: we use Support Vector Machines (SVM)...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
ICML
2008
IEEE
16 years 5 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
ICML
2005
IEEE
16 years 5 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...