Machine Learning in Computational Geometry

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Analysis of Algorithms and Complexity Theory".

Deadline for manuscript submissions: closed (15 May 2023) | Viewed by 14227

Special Issue Editors


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Department of Computer Engineering and Informatics, University of Patras, 26504 Rio Achaia, Greece
Interests: data management for smart city governance; artificial intelligence for smart cities; big data in the context of urban sustainability; machine learning for advanced digital manufacturing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computer Engineering and Informatics, University of Patras, 26504 Rio Achaia, Greece
Interests: data structures; information retrieval; data mining; bioinformatics; string algorithmic; computational geometry; multimedia databases; internet technologies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computational geometry is a discipline of computer science devoted to the study of problems which can be stated in terms of geometric objects, such as points, lines, circles, and other structures in geometric spaces.

Machine learning concerns techniques that can learn from and make predictions on data. Such techniques and algorithms are built to explore the useful pattern of the input data, which usually can be stated in terms of geometry (e.g., problems in a high-dimensional feature space). Hence, computational geometry plays a crucial and natural role in machine learning. Importantly, geometric algorithms often come with quality guaranteed solutions when dealing with high-dimensional data.

This Special Issue is particularly interested in applications of geometric algorithms in machine learning, both in theory, algorithms, and applications. We are soliciting research and review articles covering a wide range of topics on computational geometry, including (though not limited to) the following:

  • Design, analysis and computational complexity of geometric algorithms;
  • Discrete and combinatorial geometry;
  • Computational topology;
  • Geographic information systems;
  • Applications of computational geometry in any field.

Dr. Andreas Kanavos
Dr. Christos Makris
Guest Editors

Manuscript Submission Information

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Keywords

  • computational geometry
  • algorithmic geometry
  • numerical computational geometry
  • geometric modeling
  • geometric algorithms
  • computational complexity of geometric problems
  • discrete and combinatorial geometry
  • computational topology
  • combinatorial optimization
  • graph drawing

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Published Papers (3 papers)

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Research

13 pages, 305 KiB  
Article
Folding Every Point on a Polygon Boundary to a Point
by Nattawut Phetmak and Jittat Fakcharoenphol
Algorithms 2023, 16(6), 281; https://doi.org/10.3390/a16060281 - 31 May 2023
Viewed by 1739
Abstract
We consider a problem in computational origami. Given a piece of paper as a convex polygon P and a point f located within, we fold every point on a boundary of P to f and compute a region that is safe from folding, [...] Read more.
We consider a problem in computational origami. Given a piece of paper as a convex polygon P and a point f located within, we fold every point on a boundary of P to f and compute a region that is safe from folding, i.e., the region with no creases. This problem is an extended version of a problem by Akitaya, Ballinger, Demaine, Hull, and Schmidt that only folds corners of the polygon. To find the region, we prove structural properties of intersections of parabola-bounded regions and use them to devise a linear-time algorithm. We also prove a structural result regarding the complexity of the safe region as a variable of the location of point f, i.e., the number of arcs of the safe region can be determined using the straight skeleton of the polygon P. Full article
(This article belongs to the Special Issue Machine Learning in Computational Geometry)
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14 pages, 1221 KiB  
Article
Line Clipping in 3D: Overview, Techniques and Algorithms
by Dimitrios Matthes and Vasileios Drakopoulos
Algorithms 2023, 16(4), 201; https://doi.org/10.3390/a16040201 - 9 Apr 2023
Viewed by 8947
Abstract
Clipping algorithms essentially compute the intersection of the clipping object and the subject, so to go from two to three dimensions we replace the two-dimensional clipping object by the three-dimensional one (the view frustum). In three-dimensional graphics, the terminology of clipping can be [...] Read more.
Clipping algorithms essentially compute the intersection of the clipping object and the subject, so to go from two to three dimensions we replace the two-dimensional clipping object by the three-dimensional one (the view frustum). In three-dimensional graphics, the terminology of clipping can be used to describe many related features. Typically, “clipping” refers to operations in the plane that work with rectangular shapes, and “culling” refers to more general methods to selectively process scene model elements. The aim of this article is to survey important techniques and algorithms for line clipping in 3D, but it also includes some of the latest research performed by the authors. Full article
(This article belongs to the Special Issue Machine Learning in Computational Geometry)
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8 pages, 254 KiB  
Article
Higher-Order Curvatures of Plane and Space Parametrized Curves
by Mircea Crasmareanu
Algorithms 2022, 15(11), 436; https://doi.org/10.3390/a15110436 - 18 Nov 2022
Cited by 1 | Viewed by 2139
Abstract
We start by introducing and studying two sequences of curvatures provided by the higher-order derivatives of the usual Frenet equation of a given plane curve C. These curvatures are expressed by a recurrence starting with the pair [...] Read more.
We start by introducing and studying two sequences of curvatures provided by the higher-order derivatives of the usual Frenet equation of a given plane curve C. These curvatures are expressed by a recurrence starting with the pair (0,k) where k is the classical curvature function of C. Moreover, for the space curves, we succeed in introducing three recurrent sequences of curvatures starting with the triple (k,0,τ). Some kinds of helices of a higher order are defined. Full article
(This article belongs to the Special Issue Machine Learning in Computational Geometry)
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