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JMLR
2006
125views more  JMLR 2006»
9 years 11 months ago
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
Shai Shalev-Shwartz, Yoram Singer
JMLR
2006
103views more  JMLR 2006»
9 years 11 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
JMLR
2006
89views more  JMLR 2006»
9 years 11 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
JMLR
2006
147views more  JMLR 2006»
9 years 11 months ago
Spam Filtering Based On The Analysis Of Text Information Embedded Into Images
In recent years anti-spam filters have become necessary tools for Internet service providers to face up to the continuously growing spam phenomenon. Current server-side anti-spam ...
Giorgio Fumera, Ignazio Pillai, Fabio Roli
JMLR
2006
169views more  JMLR 2006»
9 years 11 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
JMLR
2006
85views more  JMLR 2006»
9 years 11 months ago
Streamwise Feature Selection
In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
JMLR
2006
150views more  JMLR 2006»
9 years 11 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
JMLR
2006
156views more  JMLR 2006»
9 years 11 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
JMLR
2006
135views more  JMLR 2006»
9 years 11 months ago
Statistical Comparisons of Classifiers over Multiple Data Sets
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Janez Demsar
JMLR
2006
112views more  JMLR 2006»
9 years 11 months ago
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
We develop kernels for measuring the similarity between relational instances using background knowledge expressed in first-order logic. The method allows us to bridge the gap betw...
Andrea Passerini, Paolo Frasconi, Luc De Raedt
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