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|Title=Optimization for Machine Learning (NIPS Workshop 2008) | |Title=Optimization for Machine Learning (NIPS Workshop 2008) | ||
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|City=Whistler | |City=Whistler | ||
|Country=Country:CA | |Country=Country:CA |
Latest revision as of 15:27, 19 October 2022
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Camera-Ready |
Venue
Whistler, Canada
Warning: Venue is missing. The map might not show the exact location.
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
- Problems with sparsity constraints
- Sparse PCA
- Non-negative matrix and tensor approximation
- Non-convex quadratic programming
- Combinatorial and Discrete Optimization example problems in ML include
- Estimating MAP solutions to discrete random fields
- Clustering and graph-partitioning
- Semi-supervised and multiple-instance learning
- Feature and subspace selection
- Stochastic, Parallel and Online Optimization example problems in ML include
- Massive data sets
- Distributed learning algorithms
- Algorithms and Techniques especially with a focus on an underlying application
- Polyhedral combinatorics, polytopes and strong valid inequalities
- Linear and higher-order relaxations
- Semidefinite programming relaxations
- Decomposition for large-scale, message-passing and online learning
- Global and Lipschitz optimization
- Algorithms for non-smooth optimization
- 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