===============================================
Call for Papers
Discrete Optimization in Machine Learning
Submodularity, Sparsity & Polyhedra
Workshop at the
23rd Annual Conference on Neural Information Processing Systems
(NIPS 2009)
http://www.discml.cc
Submission Deadline: November 6, 2009
===============================================
- We apologize for multiple postings -
Solving optimization problems with ultimately discretely solutions is
becoming increasingly important in machine learning: At the core of
statistical machine learning is to infer conclusions from data, and
when the variables underlying the data are discrete, both the tasks of
inferring the model from data, as well as performing predictions using
the estimated model are discrete optimization problems. This workshop
aims at exploring discrete structures relevant to machine learning and
techniques relevant to solving discrete learning problems.
We would like to encourage high quality submissions of short papers
relevant to the workshop topics. Accepted papers will be presented as
spotlight talks and posters. Of particular interest are new
algorithms with theoretical guarantees, as well as applications of
discrete optimization to machine learning problems in areas such as
the following:
Combinatorial algorithms
- Submodular & supermodular optimization
- Discrete convex analysis
- Pseudo-boolean optimization
- Randomized / approximation algorithms
Continuous relaxations
- Sparse approximation & compressive sensing
- Regularization techniques
- Structured sparsity models
Applications
- Graphical model inference & structure learning
- Clustering
- Feature Selection & experimental design
- Structured prediction
- Novel discrete optimization problems in ML
Submission deadline: November 6
Length & Format: max. 6 pages NIPS 2009 format
Time & Location: December 11 2009, Whistler, Canada
Submission instructions: Email to sub...@discml.cc
Organizers: Andreas Krause (California Institute of Technology),
Pradeep Ravikumar (University of Texas, Austin), Jeff A. Bilmes
(University of Washington)
_______________________________________________
uai mailing list
uai@ENGR.ORST.EDU
https://secure.engr.oregonstate.edu/mailman/listinfo/uai
