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Lipschitz decomposition is a useful tool in the design of efficient algorithms involving metric spaces. While many bounds are known for different families of finite metrics, the optimal parameters for $n$-point subsets of $\ell_p$, for $p >…

Computational Geometry · Computer Science 2026-02-23 Robert Krauthgamer , Nir Petruschka

Recently, $p$-presentation distances for $p\in [1,\infty]$ were introduced for merge trees and multiparameter persistence modules as more sensitive variations of the respective interleaving distances ($p=\infty)$. It is well-known that…

Computational Geometry · Computer Science 2025-06-09 Håvard Bakke Bjerkevik , Magnus Bakke Botnan

We introduce the convex matching distance, a novel metric for comparing functions with values in the real plane. This metric measures the maximal bottleneck distance between the persistence diagrams associated with the convex combinations…

We prove a Lipschitz extension lemma in which the extension procedure simultaneously preserves the Lipschitz continuity for two non-equivalent distances. The two distances under consideration are the Euclidean distance and, roughly…

Analysis of PDEs · Mathematics 2021-01-27 Laura Caravenna , Gianluca Crippa

We develop a stability theory for minimal projective resolutions of $\mathbf{P}$-modules, where $\mathbf{P}$ is a finite metric poset. We use the G\"ulen-McCleary distance on $\mathbf{P}$-modules together with a new complex matching…

Representation Theory · Mathematics 2026-04-14 Hideto Asashiba , Amit K. Patel

The interleaving distance is arguably the most widely used metric in topological data analysis (TDA) due to its applicability to a wide array of inputs of interest, such as (multiparameter) persistence modules, Reeb graphs, merge trees, and…

Algebraic Topology · Mathematics 2026-01-15 Astrid A. Olave , Elizabeth Munch

In 2009, Chazal et al. introduced $\epsilon$-interleavings of persistence modules. $\epsilon$-interleavings induce a pseudometric $d_I$ on (isomorphism classes of) persistence modules, the interleaving distance. The definitions of…

Computational Geometry · Computer Science 2015-05-22 Michael Lesnick

As neural networks grow in size and complexity, inference speeds decline. To combat this, one of the most effective compression techniques -- channel pruning -- removes channels from weights. However, for multi-branch segments of a model,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Alvin Wan , Hanxiang Hao , Kaushik Patnaik , Yueyang Xu , Omer Hadad , David Güera , Zhile Ren , Qi Shan

The Lipschitz extension modulus $e(M)$ of a metric space $M$ is the infimum over $L\ge 1$ such that for any Banach space $Z$ and any $C\subset M$, any 1-Lipschitz function $f:C\to Z$ can be extended to an $L$-Lipschitz function $F:M\to Z$.…

Metric Geometry · Mathematics 2024-02-14 Assaf Naor

We prove new bounds on the dimensions of distance sets and pinned distance sets of planar sets. Among other results, we show that if $A\subset\mathbb{R}^2$ is a Borel set of Hausdorff dimension $s>1$, then its distance set has Hausdorff…

Classical Analysis and ODEs · Mathematics 2019-12-17 Tamás Keleti , Pablo Shmerkin

Lipschitz constraints under L2 norm on deep neural networks are useful for provable adversarial robustness bounds, stable training, and Wasserstein distance estimation. While heuristic approaches such as the gradient penalty have seen much…

Machine Learning · Computer Science 2019-11-12 Qiyang Li , Saminul Haque , Cem Anil , James Lucas , Roger Grosse , Jörn-Henrik Jacobsen

In recent work, generalized persistence modules have proved useful in distinguishing noise from the legitimate topological features of a data set. Algebraically, generalized persistence modules can be viewed as representations for the poset…

Algebraic Topology · Mathematics 2017-10-10 Killian Meehan , David Meyer

Though Transformers have achieved promising results in many computer vision tasks, they tend to be over-confident in predictions, as the standard Dot Product Self-Attention (DPSA) can barely preserve distance for the unbounded input domain.…

Machine Learning · Computer Science 2023-07-19 Wenqian Ye , Yunsheng Ma , Xu Cao , Kun Tang

In this paper we study local error bound moduli for a locally Lipschitz and regular function via its outer limiting subdifferential set. We show that the distance of 0 from the outer limiting subdifferential of the support function of the…

Optimization and Control · Mathematics 2016-08-12 Minghua Li , Kaiwen Meng , Xiaoqi Yang

In this paper, we approach the task of determining sensitivity bounds for pose estimation neural networks. This task is particularly challenging as it requires characterizing the sensitivity of 3D rotations. We develop a sensitivity measure…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Trevor Avant , Kristi A. Morgansen

In this paper, we consider the online proximal mirror descent for solving the time-varying composite optimization problems. For various applications, the algorithm naturally involves the errors in the gradient and proximal operator. We…

Optimization and Control · Mathematics 2023-04-11 Woocheol Choi , Myeong-Su Lee , Seok-Bae Yun

Text classifiers suffer from small perturbations, that if chosen adversarially, can dramatically change the output of the model. Verification methods can provide robustness certificates against such adversarial perturbations, by computing a…

Machine Learning · Computer Science 2025-02-21 Elias Abad Rocamora , Grigorios G. Chrysos , Volkan Cevher

We present a generalization of the induced matching theorem and use it to prove a generalization of the algebraic stability theorem for $\mathbb{R}$-indexed pointwise finite-dimensional persistence modules. Via numerous examples, we show…

Algebraic Topology · Mathematics 2018-01-23 Shaun Harker , Miroslav Kramar , Rachel Levanger , Konstantin Mischaikow

Barcodes form a complete set of invariants for interval decomposable persistence modules and are an important summary in topological data analysis. The set of barcodes is equipped with a canonical one-parameter family of metrics, the…

Algebraic Topology · Mathematics 2025-11-20 Wanchen Zhao , Peter Bubenik

We introduce a new distance measure for comparing polygonal chains: the $k$-Fr\'echet distance. As the name implies, it is closely related to the well-studied Fr\'echet distance but detects similarities between curves that resemble each…

Computational Geometry · Computer Science 2019-03-07 Hugo A Akitaya , Maike Buchin , Leonie Ryvkin , Jérôme Urhausen