posted by user: stich || 3643 views || tracked by 4 users: [display]

OPT 2019 : 11th OPT Workshop on Optimization for Machine Learning

FacebookTwitterLinkedInGoogle

Link: http://opt-ml.org/
 
When Dec 14, 2019 - Dec 14, 2019
Where Vancouver, Canada
Submission Deadline Sep 30, 2019
Notification Due Oct 24, 2019
Final Version Due Dec 1, 2019
Categories    optimization   machine learning
 

Call For Papers

Optimization lies at the heart of many machine learning algorithms and enjoys great interest in our community. Indeed, this intimate relation of optimization with ML is the key motivation for the OPT series of workshops. We aim to foster discussion, discovery, and dissemination of state-of-the-art research in optimization relevant to ML.

We invite participation in the 11th International Workshop on "Optimization for Machine Learning", to be held as an independent event, co-located with NeurIPS. We invite high quality submissions for presentation as spotlights or poster presentations during the workshop. We are especially interested in participants who can contribute theory, algorithms, applications, or implementations with a machine learning focus.

All accepted contributions will be listed on the workshop webpage (though there are no archival proceedings) and are expected to be presented as a poster during the workshop. A few submissions will in addition be selected for contributed talks or for short spotlight presentations.

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

Nonconvex Optimization
-Local and global optimality theory
-The role of overparameterization
-Architecture dependent optimization techniques
-The interface of generalization and optimization
-Convex concave decompositions, D.C. programming
-Approximation Algorithms
-Other topics in nonconvex optimization

Stochastic, Parallel and Online Optimization:
-Large-scale learning, massive data sets
-Distributed and decentralized algorithms
-Distributed optimization algorithms, and parallel architectures
-Optimization using GPUs, Streaming algorithms
-Decomposition for large-scale, message-passing, and online optimization
-Stochastic approximations

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
-Other discrete optimization models and algorithms

Other optimization techniques
-Hashing based optimization, sketching techniques
-Optimization in statistics, statistical/computational tradeoffs
-Optimization on manifolds, metric spaces; optimal transport
-Polynomials, sums-of-squares, moment problems
-Optimization techniques for Reinforcement Learning

Numerical optimization
-Optimization software
-Integration with deep learning software, accelerator hardware and systems
-Crucial implementation details (architecture, language, etc.)

Looking forward to another great OPT workshop!

Related Resources

Federated Learning in IOT Cybersecurity 2021   PeerJ Computer Science - Federated Learning for Cybersecurity in Internet of Things
CVPR 2022   Computer Vision and Pattern Recognition
CFDSP 2022   2022 International Conference on Frontiers of Digital Signal Processing (CFDSP 2022)
OPT 2021   NeurIPS Workshop on Optimization for Machine Learning (OPT21)
MLDM 2022   18th International Conference on Machine Learning and Data Mining
JCRAI 2021-Ei Compendex & Scopus 2021   2021 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2021)
FAIML 2022   2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2022)
ICADCML 2022   3rd International Conference on Advances in Distributed Computing and Machine Learning - 2022
AISTATS 2022   25th International Conference on Artificial Intelligence and Statistics
blockchain_ml_iot 2021   Network and Electronics (MDPI) Joint Special Issue - Blockchain and Machine Learning for IoT: Security and Privacy Challenges