Algebraic Combinatorics in Data Science and Optimisation
A special issue of AppliedMath (ISSN 2673-9909).
Deadline for manuscript submissions: 31 July 2025 | Viewed by 387
Special Issue Editor
Interests: computational commutative algebra; discrete mathematics; combinatorics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nowadays, data science and optimization are attractive fields. There is no doubt that algebraic and combinatorial methods are extremely useful in this research field. Combinatorics, on the other hand, is a broad field, and algebraic combinatorics in particular has made tremendous progress over the past quarter century and continues to develop as a research field that organically links combinatorics and various branches of algebra. This Special Issue aims to capture the shades of algebraic combinatorics that emerge in data science and optimization research to provide new topics in algebraic combinatorics from the perspective of applied mathematics, and to give birth to a novel trend in algebraic combinatorics.
Prof. Dr. Takayuki Hibi
Guest Editor
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Keywords
- convex polytope
- finite partially ordered set
- finite graph
- simplicial complex
- statistics
- experimental design
- business acumen
- communication
- databases
- marketing
- discrete optimization
- linear programming
- integer programming
- machine learning
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