New Advance of Data Driven Optimization and AI—in Honor of Prof.Dr. Kai-Tai Fang
A special issue of Mathematics (ISSN 2227-7390).
Deadline for manuscript submissions: closed (20 September 2023) | Viewed by 3630
Special Issue Editor
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is a hot research field in recent years. The main fields of its development include deep learning, natural language processing, computer vision, intelligent robots, automatic programming, data mining, etc. The research in these fields is inseparable from the support of mathematics and statistics. AI is actually a field that closely combines mathematics, algorithm theory, and engineering practice, and its algorithms are the embodiment of mathematics, probability theory, statistics, and various mathematical theories. In simple terms, intelligence is the ability to simulate a human being, that is, in a given environment, it can improve its ability to solve problems by interacting with the environment by itself. A machine or software used to simulate this kind of intelligence is called machine learning. From the mathematical dimension, machine learning represents an optimization problem in a function space or parameter space. On the one hand, one of the foundations of AI is mathematics, so if AI wants to achieve stability, it must first solve the basic problems of mathematics; on the other hand, the development of AI has also produced important research fields for mathematics. This Special Issue focuses on the mathematics and statistics foundation and application of AI.
The topics are listed, but not limited, as follows:
- Unification algorithms, calculi and implementations;
- Equational unification and unification modulo theories;
- Unification in modal, fuzzy, temporal and description logics;
- Anti-unification/generalization;
- Conceptual knowledge acquisition;
- Data and text mining;
- Optimal design for security and privacy;
- Approximation of the number of neurons in deep neural network based on functional analysis;
- Symmetry in neural networks based on group theory;
- The relationship between input and output of neural network based on differential manifold.
Dr. Zongwei Luo
Guest Editor
Manuscript Submission Information
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Keywords
- deep learning
- neural network
- data mining
- uniform modalities
- functional analysis
- group theory
- differential manifold
