CFP: OPT 2011, NIPS Workshop on Optimization for Machine Learning

Dear Colleagues,

We invite participation in the 4th International Workshop on “Optimization for
Machine Learning”, to be held as a part of the NIPS 2011 conference.

Join us for an exciting program that includes plenary talks by:

* Stephen Boyd (Stanford University)
* Aharon Ben-Tal (Technion)
* Ben Recht (UW Madison)

OPT 2011: NIPS Workshop on Optimization for Machine Learning

Research contributions from the community are welcomed; in particular, we
invite the following two types of submissions:

(i) contributed talks and posters
(ii) open problems

To encourage authors to submit cutting-edge work, the workshop will offer a
best paper award as recognition. We request submitters of open problems to
prepare a few slides that clearly present, motivate, and explain an important
open problem or concern.

The main topics are, including, but not limited to:

* Stochastic, Parallel and Online Optimization,
– Large-scale learning, massive data sets
– Distributed algorithms
– Optimization on massively parallel architectures
– Optimization using GPUs, Streaming algorithms
– Decomposition for large-scale, message-passing and online learning
– Stochastic approximation
– Randomized algorithms

* Nonconvex Optimization,
– Nonsmooth, nonconvex optimization
– Nonconvex quadratic programming, including binary QPs
– Convex Concave Decompositions, D.C. Programming, EM
– Training of deep architectures and large hidden variable models
– Approximation Algorithms

* Algorithms and Techniques (application oriented)
– Global and Lipschitz optimization
– Algorithms for nonsmooth optimization
– Linear and higher-order relaxations
– Polyhedral combinatorics applications to ML problems

* Combinatorial Optimization
– Optimization in Graphical Models
– Structure learning
– MAP estimation in continuous and discrete random fields
– Clustering and graph-partitioning
– Semi-supervised and multiple-instance learning

* Practical techniques
– Optimization software and toolboxes
– GPU, Multicore, Distributed implementations

* Applications close to machine learning
– Sparse learning, compressed sensing, signal processing
– Computational Statistics
– Large scale scientific computing

Important Dates

* Deadline for submission of papers: 26th October 2011
* Notification of acceptance: 12th November 2011
* Final version of submission: 24th November 2011

Please note that at least one author of each accepted paper must be available
to present the paper at the workshop. Further details regarding the
submission process are available at the workshop homepage.


* Suvrit Sra, Max Planck Institute for Intelligent Systems
* Sebastian Nowozin, Microsoft Research, Cambridge, UK
* Stephen Wright, University of Wisconsin, Madison

Further Details