eISSN:
 2577-8838

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Volume 2, 2019

Volume 1, 2018

Mathematical Foundations of Computing

Call for papers


Call for Papers: special issue on “Theme Issue on kernel-based methods”

Kernel-based methods have been used for various purposes in many fields including density estimation and regression in statistics, support vector machines and learning kernels in machine learning, and mesh-free schemes in numerical analysis and uncertainty quantification. They play an essential role in finding filters and features in the recent development of deep learning and deep neural networks. The aim of this theme issue is to report recent research results on kernel-based methods, carry out interactions among researchers, discuss important research problems and directions, and promote kernel methods in various research areas.

Topics Covered

Potential topics appropriate for this special issue include, but not necessarily limited to:

Regularization schemes and deep learning
Multivariate approximation
Meshless methods
Kernel-based methods in data science, image and signal processing
Kernel-based function spaces and complexity
Kernel-based algorithms and computing

Important Dates

Submission deadline: November 30, 2019
Completion of peer reviews: February 28, 2020
Tentative publication date: May 2020

Submission Guidelines

Submitted papers will be peer-reviewed following the reviewing procedures of the journal Mathematical Foundations of Computing. They must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue. The submitted papers should follow the submission format and guidelines found at the journal webpage:
https://www.aimsciences.org/journal/A0000-0001

Guest Editors

Dr. Han Feng
City University of Hong Kong
Prof. Sergei Pereverzyev 
Austrian Academy of Sciences, Austria 
Prof. Ding-Xuan Zhou
City University of Hong Kong

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