posted by organizer: fersiniel || 10409 views || tracked by 14 users: [display]

SI: COMPUTERS & OR 2017 : Special issue on DATA ANALYTICS and OPTIMIZATION at COMPUTERS & OPERATIONS RESEARCH (Elsevier)

FacebookTwitterLinkedInGoogle

Link: https://www.journals.elsevier.com/computers-and-operations-research/call-for-papers/call-for-papers-data-analytics-and-optimization
 
When N/A
Where N/A
Submission Deadline Jul 15, 2017
Notification Due Sep 30, 2017
Final Version Due Dec 30, 2017
Categories    machine learning   optimization
 

Call For Papers

*Call for papers*

call available at: https://www.journals.elsevier.com/computers-and-operations-research/call-for-papers/call-for-papers-data-analytics-and-optimization

The interplay between Optimization and Machine Learning is a fundamental step towards the modern decision sciences in the era of Big Data.

Machine learning researchers have exploited optimization models and algorithms to build automatic knowledge discovery from data while optimization approaches have latch on to machine learning because of their wide applicability and attractive theoretical properties.

The increasing complexity, size, and variety of today’s data analytics models presents new challenges for mathematical programming and optimization, and calls for both new development and enriched resurgence of operations research methods.

Optimization models and algorithms can improve the data-driven decision models by either formulating the pattern discovery and knowledge extraction problems or defining efficient algorithms for enabling machine learning at a massive scale.

This Special issue on “Data Analytics and Optimization” aims at gathering the ongoing cross-disciplinary research by involving operation research, machine learning and statistical methods to extract essential knowledge from huge volumes of data.

*Topics of Interest*

Optimization methods for machine learning
Analytics and Intelligent Optimization
Fuzzy Optimization in machine learning
Graphs and Networks Analytics
Algorithms for statistical model learning
Mathematical problem formulations for learning and inference

These and other related methodological, theoretical, and empirical contributions are all welcome.

**IMPORTANT DATES**

Submission start: February 15th, 2017
Paper submission deadline: June 15th, 2017
Notification of Review Results: September 30th, 2017
Submission deadline for papers invited for revision: November 30th, 2017
Final decision of acceptance: December 30th, 2017
Desirable publication date: March 2018

*Guest Editors*

Elisabetta Fersini (Email - fersini@disco.unimib.it)
Francesca Guerriero (Email - francesca.guerriero@unical.it)
Enza Messina (Email - messina@disco.unimib.it)
Daniele Vigo (Email - daniele.vigo@unibo.it)

Related Resources

AIChE Spring Meeting & GCPS 2026   2026 AIChE Spring Meeting & 22nd Global Congress on Process Safety
IEEE-ICECCS 2026   2025 IEEE International Conference on Electronics, Communications and Computer Science (ICECCS 2026)
IJSC 2026   International Journal on Soft Computing - H-Index:26
AMLDS 2026   IEEE--2026 2nd International Conference on Advanced Machine Learning and Data Science
IJBISS 2026   International Journal of Business Information Systems Strategies
Ei/Scopus-ACEPE 2026   2026 3rd IEEE Asia Conference on Advances in Electrical and Power Engineering (ACEPE 2026)
AgriFood Sensors & Electronics 2026   AgriFood Sensors & Electronics From Circuits to Systems Conference
AAIML 2027   IEEE--2027 2nd International Conference on Advances in Artificial Intelligence and Machine Learning
Dairy Systems & Technology 2026   Precision Dairy Systems & Technology Conference
NeTIOT 2026   7th International Conference on Networks & IOT