Applications of Machine Learning in Large-Scale Optimization and High-Dimensional Learning

Topic Information

Dear Colleagues,

Machine Learning (ML) has found a wide range of applications in large-scale optimization and high-dimensional learning problems. Below are some notable areas where ML is applied:

1. Large-Scale Optimization: ML techniques are used to tackle complex optimization problems in various domains. These include optimizing supply chain logistics, scheduling tasks in industrial processes, and parameter tuning in machine learning algorithms;
2. Multi-Objective Optimization: ML is well suited for multi-objective optimization problems, where there are multiple conflicting objectives to be optimized simultaneously. These scenarios are common in fields such as engineering, finance, and resource allocation;
3. High-Dimensional Data Analysis: ML aids in discovering patterns in high-dimensional data. These patterns can be used in various applications, such as customer segmentation in marketing, anomaly detection, and image segmentation.

Prof. Dr. Jeng-Shyang Pan
Prof. Dr. Junzo Watada
Prof. Dr. Vaclav Snasel
Dr. Pei Hu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	-	7.2	2020	20.8 Days	CHF 1600	Submit
Buildings buildings	3.8	3.4	2011	14.6 Days	CHF 2600	Submit
Computers computers	2.8	5.4	2012	17.7 Days	CHF 1800	Submit
Drones drones	4.8	5.6	2017	17.9 Days	CHF 2600	Submit
Entropy entropy	2.7	4.9	1999	20.8 Days	CHF 2600	Submit
Symmetry symmetry	2.7	5.4	2009	16.2 Days	CHF 2400	Submit

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