JMLR Special Topic on Machine Learning and Large Scale Optimization

The Interplay of Optimization and Machine Learning Research
Kristin P. Bennett, Emilio Parrado-Hernández; 7(Jul):1265--1281, 2006.

Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola; 7(Jul):1283--1314, 2006.

Ensemble Pruning Via Semi-definite Programming
Yi Zhang, Samuel Burer, W. Nick Street; 7(Jul):1315--1338, 2006.

Linear Programs for Hypotheses Selection in Probabilistic Inference Models
Anders Bergkvist, Peter Damaschke, Marcel Lüthi; 7(Jul):1339--1355, 2006.

Bayesian Network Learning with Parameter Constraints
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao; 7(Jul):1357--1383, 2006.

Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
Matthias Heiler, Christoph Schnörr; 7(Jul):1385--1407, 2006.

Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems
Tijl De Bie, Nello Cristianini; 7(Jul):1409--1436, 2006.

An Efficient Implementation of an Active Set Method for SVMs
Katya Scheinberg; 7(Oct):2237--2257, 2006.

Maximum-Gain Working Set Selection for SVMs
Tobias Glasmachers, Christian Igel; 7(Jul):1437--1466, 2006.

Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
Luca Zanni, Thomas Serafini, Gaetano Zanghirati; 7(Jul):1467--1492, 2006.

Incremental Support Vector Learning: Analysis, Implementation and Applications
Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller; 7(Sep):1909--1936, 2006.

Building Support Vector Machines with Reduced Classifier Complexity
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste; 7(Jul):1493--1515, 2006.

Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Olvi L. Mangasarian; 7(Jul):1517--1530, 2006.

Linear Programming Relaxations and Belief Propagation -- An Empirical Study
Chen Yanover, Talya Meltzer, Yair Weiss; 7(Sep):1887--1907, 2006.
[abs][pdf]    [data]

Large Scale Multiple Kernel Learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf; 7(Jul):1531--1565, 2006.

Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
Shai Shalev-Shwartz, Yoram Singer; 7(Jul):1567--1599, 2006.
[abs][pdf]    [code]

Kernel-Based Learning of Hierarchical Multilabel Classification Models
Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-Taylor; 7(Jul):1601--1626, 2006.

Structured Prediction, Dual Extragradient and Bregman Projections
Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan; 7(Jul):1627--1653, 2006.

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