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|Title=Optimization for Machine Learning (NIPS Workshop 2008) | |Title=Optimization for Machine Learning (NIPS Workshop 2008) | ||
|Type=Workshop | |Type=Workshop | ||
| − | |||
|Homepage=opt2008.kyb.tuebingen.mpg.de/ | |Homepage=opt2008.kyb.tuebingen.mpg.de/ | ||
|City=Whistler | |City=Whistler | ||
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|Start Date=Dec 12, 2008 | |Start Date=Dec 12, 2008 | ||
|End Date=Dec 13, 2008 | |End Date=Dec 13, 2008 | ||
| + | |Academic Field=Machine Learning | ||
}} | }} | ||
Revision as of 13:50, 24 August 2022
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
