posted by organizer: enino84 || 3300 views || tracked by 4 users: [display]

COMIP-IJAI 2017 : Special Issue of IJAI - Combinatorial Optimization Methods for Inverse Problems

FacebookTwitterLinkedInGoogle

Link: http://www.ceser.in/ceserp/index.php/ijai/about/editorialPolicies#custom-1
 
When N/A
Where N/A
Abstract Registration Due Dec 30, 2016
Submission Deadline Feb 28, 2017
Notification Due Apr 30, 2017
Final Version Due May 30, 2017
Categories    computer science   inverse problems   combinatorial optimization   data assimilation
 

Call For Papers

Inverse Problems are problems related to parameter and state estimation (inputs) based on (possibly) real-noisy observations (perturbed outputs). This kind of problems is widely occurred in many scientific fields. For instance, the application fields range from parameter estimation in Partial Differential Equations to state estimation in Data Assimilation. Usually, the estimation process is performed by making use of Bayesian inference wherein errors associated to priors and observations are assumed to follow some known probability distribution. Since the estimation is based on a stochastic process, commonly, the posterior estimate is chosen to be the Maximum A Posteriori (MAP) estimate, this is, the sample from the posterior distribution which maximizes the posterior probability. Depending on the number of components (parameters) to be estimated and the quality of the prior sample, the posterior estimate can provide meaningful or meaningless information about the true set of parameters and their corresponding uncertainty. This is clear since the MAP is nothing but a sample from the posterior distribution and depending on its unknown bias, for instance, it can be possible to improve the predicted parameters by taking another sample from the posterior distribution. This is a particular case which opens the door to stochastic algorithms in order to improve the quality of predicted values based on Bayesian inferences.



Papers are welcome on all aspects of Combinatorial Optimization applied to Inverse Problems, including, but not restricted to:



• Markov Chain Monte Carlo (MCMC) methods for computing posterior estimates.

• Combinatorial optimization in Bayesian inference.

• Local Search methods in Data Assimilation.

• Meta-heuristics in Covariance Matrix estimation.

• Stochastic Methods for Uncertainty Quantification.

• Stochastic Algorithms for Network Design.

• Decision Support Systems based on historical data.



Important Dates:



December 30, 2016: Expression of interest (title and abstract to guest editors)

February 28, 2017: Full manuscript and cover letter

April 30, 2017: Review comments and decision

May 30, 2017: Revised, final manuscript



Paper Submission System:



EasyChair [ https://easychair.org/conferences/?conf=ijaicomip2017 ]


Guest Editors:



Elias D. Nino-Ruiz, Ph.D.

Assistant Professor

Department of Computer Science

Universidad del Norte

Email: enino@uninorte.edu.co

Website: https://sites.google.com/a/vt.edu/eliasnino/

Barranquilla, Colombia



Xinwei Deng, Ph.D.

Associate Professor

Department of Statistics

Virginia Tech

Email: xdeng@vt.edu

Website: www.stat.vt.edu/people/faculty/Deng-Xinwei.html

Blacksburg, VA 24060, USA



Ivan Saavedra Antolínez, Ph.D.

Director of Professional Services

Competitive Insight, LLC

Email: isaavedra@ci-advantage.com

Website: https://www.linkedin.com/in/ivan-saavedra-antolinez-58111423/en

Atlanta, GA 30080, USA



Yezid Donoso, Ph.D.

Associate Professor

Department of Computer Science

Universidad del los Andes

Email: ydonoso@uniandes.edu.co

Website: https://sistemasacademico.uniandes.edu.co/~ydonoso/

Bogota, Colombia



-----------------------------



International Journal of Artificial Intelligence” does not want any publication fee for the International Journal of Artificial Intelligence.

But all authors of papers published in special issues need to pay a fee (which may be approx. 40 EUR) to download their paper after the publication in the journal.



----------------------------

Related Resources

ICS 2018   the 32nd ACM International Conference on Supercomputing
LOPAL 2018   International Conference on Learning and Optimization Algorithms: Theory and Applications
IEEE TETCI 2018   IEEE Transactions on Emerging Topics in Computational Intelligence Special Issue on Computational Intelligence in Data-Driven Optimization
SIGI 2017   3rd International Conference on Signal and Image Processing
ICMLC - Ei 2018   2018 10th International Conference on Machine Learning and Computing (ICMLC 2018)--ACM, Ei Compendex and Scopus
FM 2018   22nd International Symposium on Formal Methods
ICCAI 2018--ACM, Ei, Scopus 2018   ACM--2018 International Conference on Computing and Artificial Intelligence (ICCAI 2018)--Ei Compendex and Scopus
MOSIM 2018   12th International Conference on Modelling, Optimization and Simulation
ICISDM--IEEE Xplore, Ei and Scopus 2018   2018 2nd International Conference on Information System and Data Mining (ICISDM 2018)--IEEE Xplore, Ei and Scopus
LICS 2018   Logic in Computer Science