Special session on Non-iterative Approaches in Learning (Including comparative studies with iterative methods)

2018 IEEE World Congress on Computational Intelligence (WCCI 2018)
Rio de Janeiro, BRAZIL, 08-13 July 2018 - http://www.ecomp.poli.br/~wcci2018/

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DESCRIPTION:
Optimization, which plays a central role in learning, has received considerable attention from academics, researchers, and domain workers. Many optimization problems in machine learning can be tackled with non-iterative approaches, which can be presented in closed-form manner. Those methods are in general computationally faster than iterative solutions and less sensitive to parameter settings. Even though non-iterative methods have attracted much attention in recent years, there exists a performance gap when compared with older methods and other competing paradigms. This special session aims to bridge this gap.
The first target of this special session is to present the recent advances of non-iterative solutions in learning. Secondly, the focus is on promoting the concepts of non-iterative optimization with respect to counterparts, such as gradient-based methods and derivative-free iterative optimization techniques. Besides the dissemination of the latest research results on non-iterative algorithms, it is also expected that this special session will cover some practical applications, present some new ideas and identify directions for future studies.
Original contributions, comparative studies with both iterative and non-iterative methods are welcome. Typical paradigms include (but not limited to) random vector functional link (RVFL), Echo State Networks (ESN), kernel ridge regression (KRR), random forests (RF), etc…
The topics of the special session include, but are not limited to:
Methods with and without randomization
Regression, classification and time series analysis
Kernel methods such as kernel ridge regression, kernel adaptive filters, etc.
Feedforward, recurrent, multilayer, deep and other structures.
Ensemble learning
Moore-Penrose pseudo inverse, SVD and other solution procedures.
Gaussian Process regression
Non-iterative methods for large-scale problems with and without kernels
Theoretical analysis of non-iterative methods
Comparative studies with competing iterative methods
Applications of non-iterative solutions in domains such as power systems, biomedical, finance, signal processing, big data and all other areas

Important Dates
15th January 2018 – paper submission deadline
15th March 2018 – Paper acceptance notification
8-13 July 2018 – IEEE WCCI 2018 conference, Rio de Janeiro, Brazil

Paper Submission
Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of WCCI 2018. Authors who submit papers to this session are invited to mention it in the form during the submission. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures of the other papers.

Organizers
Dr P. N. Suganthan, Nanyang Technological University, Singapore. epnsugan@ntu.edu.sg
Dr. Filippo Maria Bianchi, UiT the Arctic University of Norway, Tromsø, filippo.m.bianchi@uit.no

Journal Extension
The best papers submitted to the Special Session will be invited for a journal extension within the Special Issue “Non-Iterative Learning Approaches and Their Applications” on the journal Cognitive Computation, Springer (https://link.springer.com/journal/12559).
Cognitive Computation (impact factor 3.44) is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving bio-inspired computational accounts of all aspects of natural and artificial cognitive systems.​

Link to PDF version of CfP: https://drive.google.com/open?id=1LEu22zA2XHXcADEwbedsTmAAW_uSn56l