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Given a filtration of simplicial complexes, one usually applies persistent homology and summarizes the results in barcodes. Then, in order to extract statistical information from these barcodes, one needs to compute statistical indicators…

Algebraic Topology · Mathematics 2024-10-08 Alessandro Bravetti , Martín Mijangos , Pablo Padilla

Structured prediction tasks in machine learning involve the simultaneous prediction of multiple labels. This is typically done by maximizing a score function on the space of labels, which decomposes as a sum of pairwise elements, each…

Machine Learning · Computer Science 2014-09-23 Amir Globerson , Tim Roughgarden , David Sontag , Cafer Yildirim

A construction of Partial Maximum Distance Separable (PMDS) and Sector-Disk (SD) codes extending RAID 5 with two extra parities is given, solving an open problem. Previous constructions relied on computer searches, while our constructions…

Information Theory · Computer Science 2013-05-02 Mario Blaum

We apply the semidefinite programming method to derive bounds for projective codes over a finite field.

Information Theory · Computer Science 2013-11-05 Christine Bachoc , Alberto Passuello , Frank Vallentin

Sliced Wasserstein (SW) distances offer an efficient method for comparing high-dimensional probability measures by projecting them onto multiple 1-dimensional probability distributions. However, identifying informative slicing directions…

Machine Learning · Computer Science 2025-06-04 Navid NaderiAlizadeh , Darian Salehi , Xinran Liu , Soheil Kolouri

Multiparameter persistence is a natural extension of the well-known persistent homology, which has attracted a lot of interest. However, there are major theoretical obstacles preventing the full development of this promising theory. In this…

Algebraic Topology · Mathematics 2020-08-27 Jacek Brodzki , Matthew Burfitt , Mariam Pirashvili

Despite the success of the popular kernelized support vector machines, they have two major limitations: they are restricted to Positive Semi-Definite (PSD) kernels, and their training complexity scales at least quadratically with the size…

Machine Learning · Computer Science 2014-05-28 Omid Aghazadeh , Stefan Carlsson

A novel uniform circular array (UCA) based near-field (NF) integrated sensing and communication (ISAC) framework is proposed, where the Cylindrical coordinate is invoked to evaluate the joint positioning performance. The joint squared…

Signal Processing · Electrical Eng. & Systems 2025-06-03 Na Xue , Xidong Mu , Yue Chen , Yuanwei Liu

Sparsely spread code division multiple access (SCDMA) is a promising non-orthogonal multiple access technique for future wireless communications. In this paper, we propose a novel trainable multiuser detector called sparse trainable…

Information Theory · Computer Science 2019-10-24 Satoshi Takabe , Yuki Yamauchi , Tadashi Wadayama

In this paper, we first propose a spatial-temporal coupled risk assessment paradigm by constructing a three-dimensional spatial-temporal risk field (STRF). Specifically, we introduce spatial-temporal distances to quantify the impact of…

Optimization and Control · Mathematics 2026-03-31 Guodong Ma , Baofeng Sun , Hongchao Liang , Wenyu Yang , Huxing Zhou

Symbol-pair code is a new coding framework which is proposed to correct errors in the symbol-pair read channel. In particular, maximum distance separable (MDS) symbol-pair codes are a kind of symbol-pair codes with the best possible…

Information Theory · Computer Science 2016-08-10 Shuxing Li , Gennian Ge

The complex of curves $\mathcal{C}(S_g)$ of a closed orientable surface of genus $g \geq 2$ is the simplicial complex having its vertices, $\mathcal{C}^0(S_g)$, are isotopy classes of essential curves in $S_g$. Two vertices co-bound an edge…

Geometric Topology · Mathematics 2015-08-14 Paul Glenn , William W. Menasco , Kayla Morrell , Matthew Morse

A powerful and flexible approach to structured prediction consists in embedding the structured objects to be predicted into a feature space of possibly infinite dimension by means of output kernels, and then, solving a regression problem in…

Machine Learning · Statistics 2020-11-03 Luc Brogat-Motte , Alessandro Rudi , Céline Brouard , Juho Rousu , Florence d'Alché-Buc

We introduce new distance measures for comparing straight-line embedded graphs based on the Fr\'echet distance and the weak Fr\'echet distance. These graph distances are defined using continuous mappings and thus take the combinatorial…

Computational Geometry · Computer Science 2019-09-12 Hugo A. Akitaya , Maike Buchin , Bernhard Kilgus , Stef Sijben , Carola Wenk

Multidimensional scaling is a statistical process that aims to embed high dimensional data into a lower-dimensional space; this process is often used for the purpose of data visualisation. Common multidimensional scaling algorithms tend to…

Machine Learning · Computer Science 2022-02-25 Pierre Lambert , Cyril de Bodt , Michel Verleysen , John Lee

As estimators of location parameters, univariate trimmed means are well known for their robustness and efficiency. They can serve as robust alternatives to the sample mean while possessing high efficiencies at normal as well as heavy-tailed…

Statistics Theory · Mathematics 2007-06-13 Yijun Zuo

Diffusion state distance (DSD) is a metric on the vertices of a graph, motivated by bioinformatic modeling. Previous results on the convergence of DSD to a limiting metric relied on the definition being based on symmetric or reversible…

Probability · Mathematics 2015-02-26 Neal Madras

Simulated tempering is popular method of allowing MCMC algorithms to move between modes of a multimodal target density {\pi}. One problem with simulated tempering for multimodal targets is that the weights of the various modes change for…

Computation · Statistics 2019-02-12 Nicholas G. Tawn , Gareth O. Roberts , Jeffrey S. Rosenthal

After recalling the definition of codes as modules over skew polynomial rings, whose multiplication is defined by using an automorphism and a derivation, and some basic facts about them, in the first part of this paper we study some of…

Information Theory · Computer Science 2015-07-13 Luis Felipe Tapia Cuitiño , Andrea Luigi Tironi

This paper introduces an efficient algorithm for persistence diagram computation, given an input piecewise linear scalar field $f$ defined on a $d$-dimensional simplicial complex $K$, with $d \leq 3$. Our work revisits the seminal algorithm…

Machine Learning · Computer Science 2023-01-16 Pierre Guillou , Jules Vidal , Julien Tierny