Optimization and Machine Learning

Dear Colleagues,

We are pleased to invite you to submit your research to be considered for publication in a Special Issue of AppliedMath, focused on the latest advances in optimization and machine learning. The goal of this Special Issue is to showcase the latest advances in this field and to provide a platform for researchers to share their promising findings.

Optimization and machine learning (ML) have become two of the most popular issues in the last decade. ML provides a variety of tricks for data preprocessing, feature extraction, model selection, etc., whereas optimization algorithms offer elementary techniques for the construction of mathematical models and parameter fitting of ML techniques. Arising from the deep integration of optimization and ML, excellent optimization-based ML algorithms and efficient ML-assisted optimization algorithms can be developed to address the challenges of scientific research and engineering applications in the big data era.

In this Special Issue, we invite and welcome reviews and original papers about theoretical and practical studies of ML and optimization algorithms, including excellent ML algorithms based on novel optimization techniques and optimization algorithms promoted by ML strategies.

Dr. Yu Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AppliedMath is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.