MOD 2017: 3rd International Conference on Machine learning, Optimization & big Data SIAF Learning Village - Tuscany Volterra (Pisa), Italy, September 14-17, 2017 |
Conference website | http://www.taosciences.it/mod/ |
Submission link | https://easychair.org/conferences/?conf=mod2017 |
Abstract registration deadline | May 31, 2017 |
Submission deadline | May 31, 2017 |
Submission Guidelines
The International Conference on Machine learning, Optimization, and big Data (MOD) has established itself as a premier inter- and multi- disciplinary conference in machine learning, computational optimization and data science. It provides an international forum for presentation of original multidisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences.
Please prepare your paper using the Lecture Notes in Computer Science (LNCS) template, which is available
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0
Papers must be submitted in PDF.
MOD 2017 Types of Submissions
When submitting a paper to MOD 2017, authors are required to select
one of the following four types of papers:
Long paper: original novel and unpublished work (max. 12 pages in Springer LNCS format);
Short paper: an extended abstract of novel work (max. 4 pages);
Work for oral presentation only (no page restriction; any format).
For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the workshop;
Work for poster presentation only. The poster format for the
presentation is A0 (118.9 cm high and 84.1 cm wide, respectively 46.8 x 33.1 inch).
MOD 2017 Post-Proceedings
All accepted long papers will be published in a volume of the series 'Lecture Notes in Computer Science' from Springer after the Workshop.
Instructions for preparing and submitting the final versions (camera-ready papers) of all accepted papers will be available later on.
All the other papers (short papers, abstract of the oral presentations, poster presentations) will be published on the MOD 2017 web site.
All papers must be submitted using EasyChair: https://easychair.org/conferences/?conf=lod2018
Submission deadline: March 31, 2018
Any questions regarding the submission process can be sent to conference organizers: lod@icas.xyz
List of Topics
Topics of interest include, but are not limited to:
- Foundations, algorithms, models and theory of data science, including big data mining.
- Machine learning and statistical methods for big data.
- Multi-objective optimization.
- Big data Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
- Big Data mining systems and platforms, and their efficiency, scalability, security and privacy.
- Computational optimization.
- Optimization algorithms for Real World Applications.
- Optimization for Big Data.
- Optimization and Machine Learning.
- Big Data mining for modeling, visualization, personalization, and recommendation.
- Big Data mining for cyber-physical systems and complex, time-evolving networks.
- Applications in social sciences, physical sciences, engineering, life sciences, synthetic biology, systems biology, bioinformatics, web, marketing, finance, precision medicine, health informatics, medicine, control engineering and other domains.
- Industrial applications of Machine Learning, Optimization and Big Data.
We particularly encourage submissions in emerging topics of high importance such as data quality, deep learning, time-evolving networks, large multi-objective optimization, quantum optimization, big data mining and analytics, cyber-physical systems, and heterogeneous data integration and mining.
Committees
Program Committee
Organizing committee
General Chair
- Renato Umeton, Harvard University, USA
Program Chairs
- Giovanni Giuffrida, University of Catania, Italy & Neodata Group
- Giuseppe Nicosia, University of Catania, Italy
- Panos Pardalos, University of Florida, USA
Invited Speakers
- Ruslan Salakhutdinov, Machine Learning Department, School of Computer Science at Carnegie Mellon University, USA. Director of AI Research at Apple.
-
Georgios Giannakis, Department of Electrical and Computer Engineering, University of Minnesota, Director of Digital Technology Center, USA (TBC)
-
Yi-Ke Guo, Department of Computing, Faculty of Engineering, Imperial College London, UK Founding Director of Data Science Institute.
- Jun Pei, Hefei University of Technology, China
Tutorials
- “Tutorial on Scalable Data Mining on Cloud Computing Systems”, Domenico Talia, University of Calabria, Italy
-
“Mathematical Analysis of Nature-Inspired Algorithms”, Xin–She Yang, Middlesex University London, UK
Special Sessions
- "Metaheuristics and Multi-Objective optimization for Big Data"
Clarisse Dhaenens, University of Lille, France
Laetitia Jourdan, University of Lille, France
https://sites.google.com/view/mmo-bd2017/
- "Industrial Session on Machine Learning, Optimization and Data Science for Real-World Applications"
Ilaria Bordino, Marco Firrincieli, Fabio Fumarola, and Francesco Gullo, UniCredit R&D, Italy
Venue
The conference will be held in the SIAF Learning Village - Volterra (Pisa) Tuscany
SP del monte Volterrano
Localita' “Il Cipresso”
56048 Volterra (Pisa), Tuscany, Italy
Phone: (+39) 0588 81266
Fax.: (+39) 0588 86414
email: info@siafvolterra.eu
web: www.siafvolterra.eu
Contact
All questions about submissions should be emailed to modworkshop2017@gmail.com - http://www.taosciences.it/mod/