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OPT 2008 : Optimization for Machine Learning (NIPS Workshop 2008) | |||||||||||||||
Link: http://opt2008.kyb.tuebingen.mpg.de/ | |||||||||||||||
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Call For Papers | |||||||||||||||
We invite high quality submissions for presentation as talks or posters during the workshop. We are especially interested in participants who can contribute in the following areas:
* Non-Convex Optimization example problems in ML include o Problems with sparsity constraints o Sparse PCA o Non-negative matrix and tensor approximation o Non-convex quadratic programming * Combinatorial and Discrete Optimization example problems in ML include o Estimating MAP solutions to discrete random fields o Clustering and graph-partitioning o Semi-supervised and multiple-instance learning o Feature and subspace selection * Stochastic, Parallel and Online Optimization example problems in ML include o Massive data sets o Distributed learning algorithms * Algorithms and Techniques especially with a focus on an underlying application o Polyhedral combinatorics, polytopes and strong valid inequalities o Linear and higher-order relaxations o Semidefinite programming relaxations o Decomposition for large-scale, message-passing and online learning o Global and Lipschitz optimization o Algorithms for non-smooth optimization o Approximation Algorithms The above list is not exhaustive, and we welcome submissions on highly related topics too. * Deadline for submission of papers: 17th October 2008 * Notification of acceptance: 7th November 2008 * Final version of submission: 20th November 2008 * Workshop date: 12th or 13th December 2008 |
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