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MaLOTA 2015 : Machine Learning and Optimization: Trends and Applications | |||||||||||||||
Link: http://iccmit.net/SpecialSessionProposal.html | |||||||||||||||
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Call For Papers | |||||||||||||||
Call for Papers on ICCMIT 2015:
“MaLOTA: Machine Learning and Optimization: Trends and Applications” Objective and Motivation Machine learning is a concept which aims to learn from given data to make accurate predictions and intelligent decisions from this data. This concept is being used decades ago in many applications such as medical applications, biometric authentication, image retrieval, and others. Since the emerging of the Big Data, obtained from different field such as meteorology, genomics, finance, healthcare, social media and web data, the importance of the machine learning became very crucial for the decision makers. Optimization is one of the statistical learning approaches. It could be used in various applications to find the minimal cost, maximal profit, minimal error, optimal design, and others. It has a vital role in designing smart/intelligent systems, e.g. recommender systems, search engines, image retrieval/recognition, computer vision and others. The advance of these systems requires the development of new optimization techniques to enhance the learning algorithms of the applied machine learning techniques. In general, optimization provide offers a valuable framework for reasoning about, formulating, analyzing, and solving different problems in machine learning. The aim of this session is to attract researchers and practitioners from academia and industry, and provide a discussion environment in order to share their experiences of the state-of-the-art in optimization relevant to machine learning Scope and Interests Machine Learning and optimization are currently very important techniques for many computing applications. Examples of these applications include data-mining, data analytics and features extraction of Big Data, information retrieval, speech recognition, computer vision. They can also be used to improve the performance of security, and privacy techniques. The session welcomes Submissions must be original and should not have been published previously. Topics of interest include but are not limited to: • Novel machine learning techniques • Novel optimization algorithms and its application in machine learning application • Crowd-sourcing and machine learning • Big data analytics based on machine learning techniques • Theoretical of machine learning and optimization algorithms • Nature inspired machine learning algorithms • Evolution-based machine learning approaches • Biological inspired Optimization • Large Scale Optimization • New feature extraction techniques Paper Submission Important Dates The authors are invited to submit their contributions formatted according to the submission templates posted on the ICCMIT 2015 website: http://www.iccmit.net/. Submitted papers will be refereed by at least two reviewers for quality, correctness, originality, and relevance. All accepted papers will be submitted for indexing by ISI, SCOPUS, and Google Scholar. Paper abstract submission: until January 30, 2015 Notification of acceptance: February 15, 2015 Final paper submission and authors camera ready: March 30, 2015 Conference Dates: April 20-22, 2015 Session Organizers: Chair: Prof. Aboul Ella Hassanien Faculty of Computers and Information Science Cairo University, Cairo, Egypt Beni-Suef University, Beni-suef, Egypt Scientific Research Group in Egypt (www.egyptscience.net) E-mail: aboitcairo@gmail.com Co-chair: Dr. Tarek Gaber Assistant Professor Department of Computer Science Faculty of Computers & Informatics Suez Canal University, Old Campus, Ismailia, Egypt. Member at SRGE Research Group. Postdoctoral Fellow at VSB-Technical University Ostrava, Ostrava, Czech. tmgaber@gmail.com Co-chair Dr. Mohamed Mostafa Fouad Assistant Professor Arab Academy for Science, Technology, and Maritime Transport, Cairo, Egypt Member of SRGE Research Group. Postdoctoral Fellow at VSB-Technical University of Ostrava, Ostrava, Czech Republic. Mohamed_mostafa@aasy.edu |
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