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The classic Voronoi cells can be generalized to a higher-order version by considering the cells of points for which a given $k$-element subset of the set of sites consists of the $k$ closest sites. We study the structure of the $k$-order…

Metric Geometry · Mathematics 2019-06-14 Juan Enrique Martínez-Legaz , Vera Roshchina , Maxim Todorov

With the present paper we conclude the presentation of a semianalytical model of hierarchical clustering of bound virialized objects formed by gravitational instability from a random Gaussian field of density fluctuations. In paper I, we…

Astrophysics · Physics 2009-10-28 Alberto Manrique , Eduard Salvador-Sole

We study the two-dimensional geometric knapsack problem for convex polygons. Given a set of weighted convex polygons and a square knapsack, the goal is to select the most profitable subset of the given polygons that fits non-overlappingly…

Data Structures and Algorithms · Computer Science 2020-08-03 Arturo Merino , Andreas Wiese

The conventional pose estimation of a 3D object usually requires the knowledge of the 3D model of the object. Even with the recent development in convolutional neural networks (CNNs), a 3D model is often necessary in the final estimation.…

Robotics · Computer Science 2019-01-01 Zhongang Cai , Cunjun Yu , Quang-Cuong Pham

Voronoi tessellation, also known as Voronoi diagram, is an important computational geometry technique that has applications in various scientific disciplines. It involves dividing a given space into regions based on the proximity to a set…

Computational Geometry · Computer Science 2024-12-17 Sergei Shumilin , Alexander Ryabov , Serguei Barannikov , Evgeny Burnaev , Vladimir Vanovskii

Object detection is a critical part of visual scene understanding. The representation of the object in the detection task has important implications on the efficiency and feasibility of annotation, robustness to occlusion, pose, lighting,…

Computer Vision and Pattern Recognition · Computer Science 2019-07-31 Li Ding , Lex Fridman

We present techniques for speeding up the test-time evaluation of large convolutional networks, designed for object recognition tasks. These models deliver impressive accuracy but each image evaluation requires millions of floating point…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Remi Denton , Wojciech Zaremba , Joan Bruna , Yann LeCun , Rob Fergus

The recent advancements in point cloud learning have enabled intelligent vehicles and robots to comprehend 3D environments better. However, processing large-scale 3D scenes remains a challenging problem, such that efficient downsampling…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Hongcheng Yang , Dingkang Liang , Dingyuan Zhang , Zhe Liu , Zhikang Zou , Xingyu Jiang , Yingying Zhu

Convolutional neural networks have emerged as the leading method for the classification and segmentation of images. In some cases, it is desirable to focus the attention of the net on a specific region in the image; one such case is the…

Computer Vision and Pattern Recognition · Computer Science 2017-09-12 Sagi Eppel

I present a regression algorithm that provides a continuous, piecewise-smooth function approximating scattered data. It is based on composing and blending linear functions over Voronoi cells, and it scales to high dimensions. The algorithm…

Computational Geometry · Computer Science 2025-10-07 Shankar Prasad Sastry

Quantitative evaluations of differences and/or similarities between data samples define and shape optimisation problems associated with learning data distributions. Current methods to compare data often suffer from limitations in capturing…

Machine Learning · Computer Science 2024-01-23 Deborah Pelacani Cruz , George Strong , Oscar Bates , Carlos Cueto , Jiashun Yao , Lluis Guasch

We propose a first order algorithm, a modified version of FISTA, to solve an optimization problem with an objective function that is a sum of a possibly nonconvex function, with Lipschitz continuous gradient, and a convex function which can…

Optimization and Control · Mathematics 2025-08-20 Chee-Khian Sim

In this paper we present several results on the expected complexity of a convex hull of $n$ points chosen uniformly and independently from a convex shape. (i) We show that the expected number of vertices of the convex hull of $n$ points,…

Computational Geometry · Computer Science 2011-11-24 Sariel Har-Peled

The increasing availability of geometric data has motivated the need for information processing over non-Euclidean domains modeled as manifolds. The building block for information processing architectures with desirable theoretical…

Signal Processing · Electrical Eng. & Systems 2022-11-22 Zhiyang Wang , Luana Ruiz , Alejandro Ribeiro

A wide variety of methods have been used to compute percolation thresholds. In lattice percolation, the most powerful of these methods consists of microcanonical simulations using the union-find algorithm to efficiently determine the…

Statistical Mechanics · Physics 2012-12-11 Stephan Mertens , Cristopher Moore

We consider the following geometric optimization problem: find a maximum-area rectangle and a maximum-perimeter rectangle contained in a given convex polygon with $n$ vertices. We give exact algorithms that solve these problems in time…

Computational Geometry · Computer Science 2014-10-08 Sergio Cabello , Otfried Cheong , Christian Knauer , Lena Schlipf

We study the structure of the set of all possible affine hyperplane sections of a convex polytope. We present two different cell decompositions of this set, induced by hyperplane arrangements. Using our decomposition, we bound the number of…

Combinatorics · Mathematics 2025-06-02 Marie-Charlotte Brandenburg , Jesús A. De Loera , Chiara Meroni

In this paper we consider the fundamental operations dilation and erosion of mathematical morphology. Many powerful image filtering operations are based on their combinations. We establish homomorphism between max-plus semi-ring of integers…

Image and Video Processing · Electrical Eng. & Systems 2023-05-05 Vivek Sridhar , Keyvan Shahin , Michael Breuß , Marc Reichenbach

Most modern convolutional neural networks (CNNs) used for object recognition are built using the same principles: Alternating convolution and max-pooling layers followed by a small number of fully connected layers. We re-evaluate the state…

Machine Learning · Computer Science 2015-04-14 Jost Tobias Springenberg , Alexey Dosovitskiy , Thomas Brox , Martin Riedmiller

In this paper, we study the persistent homology of the offset filtration of algebraic varieties. We prove the algebraicity of two quantities central to the computation of persistent homology. Moreover, we connect persistent homology and…

Algebraic Geometry · Mathematics 2019-08-21 Emil Horobet , Madeleine Weinstein
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