Intelligent Computing and Optimization

Dear Colleagues,

Intelligent computing has greatly expanded the scope of computing, extending it from traditional computing on data to increasingly heterogeneous computing paradigms. At the same time, the majority of machine-learning methods are based on optimization theory and optimization algorithms, minimizing the intercluster distances or maximizing the Rand index in the cluster analysis, minimizing error in the regression, minimizing error rate in classification problems, etc.  Optimization problems arising in machine learning are often large-scale and multimodal, and the efficiency of specific optimization algorithms strongly depends on the data set. These difficulties require special computation techniques such as parallelizing, hardware implementation of the computation, self-configuring capabilities of the algorithms, and the hybridization of different and diverse approaches: mathematically provable/heuristic methods, discrete/continuous optimization, etc. Self-configuration requires optimizing the efficiency of the algorithm, which solves the machine-learning or other optimization problem. Moreover, the necessity to increase the efficiency of optimization algorithms can lead to the use of machine-learning algorithms embedded into optimization algorithms.

This Special Issue aims to be a platform to share the recent advances in topics such as (non-exhaustive list):

• AutoML, self-configuring, adaptive and self-adjusting methods for optimization and machine learning;
• Methods of optimization and machine learning intended for hardware implementation;
• Mathematical optimization;
• Multiobjective optimization;
• Evolutionary computation;
• Fuzzy systems;
• Parallel algorithms for optimization and machine learning;
• Hybrid optimization algorithms and algorithmic combinations;
• Optimizing artificial neural networks;
• Optimization software and decision support systems;
• Applications of intelligent computing.

Prof. Dr. Lev Kazakovtsev
Prof. Dr. Predrag S. Stanimirovic
Guest Editors

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• intelligent computing
• optimization
• AutoML
• self-configuring optimization algorithms
• evolutionary computation
• hybrid optimization
• gradient neural networks