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When $S$ is a closed, orientable surface with genus $g(S) \geq 2$, we show that the automorphism group of the compression body graph $\mathcal{CB}(S)$ is the mapping class group. Here, vertices are compression bodies with exterior boundary…

Geometric Topology · Mathematics 2024-03-11 Ian Biringer , Nicholas G. Vlamis

Rationale discovery is defined as finding a subset of the input data that maximally supports the prediction of downstream tasks. In the context of graph machine learning, graph rationale is defined to locate the critical subgraph in the…

Machine Learning · Computer Science 2025-01-28 Zhe Xu , Menghai Pan , Yuzhong Chen , Huiyuan Chen , Yuchen Yan , Mahashweta Das , Hanghang Tong

We propose a geometric assumption on nonnegative data matrices such that under this assumption, we are able to provide upper bounds (both deterministic and probabilistic) on the relative error of nonnegative matrix factorization (NMF). The…

Machine Learning · Statistics 2017-08-02 Zhaoqiang Liu , Vincent Y. F. Tan

We prove Nielsen realisation for finite subgroups of the groups of untwisted outer automorphisms of RAAGs in the following sense: given any graph $\Gamma$, and any finite group $G\leqslant \mathrm{U}^0(A_\Gamma) \leqslant…

Geometric Topology · Mathematics 2019-01-31 Sebastian Hensel , Dawid Kielak

We construct finite-dimensional projective representations of the mapping class groups of compact connected oriented surfaces having one boundary component using stated skein algebras.

Quantum Algebra · Mathematics 2022-08-29 Julien Korinman

Graph Neural Networks (GNNs) have received increasing attention due to their ability to learn from graph-structured data. To open the black-box of these deep learning models, post-hoc instance-level explanation methods have been proposed to…

Machine Learning · Computer Science 2024-02-08 Rundong Huang , Farhad Shirani , Dongsheng Luo

Matrix factorization is a well-studied task in machine learning for compactly representing large, noisy data. In our approach, instead of using the traditional concept of matrix rank, we define a new notion of link-rank based on a…

Machine Learning · Statistics 2018-05-02 Pouya Pezeshkpour , Carlos Guestrin , Sameer Singh

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix factorization techniques such as…

Statistical Mechanics · Physics 2025-07-30 Yukino Terui , Yuka Inoue , Yohei Hamakawa , Kosuke Tatsumura , Kazue Kudo

We show that the pure mapping class group $\mathcal{N}_{g}^{k}$ of a non-orientable closed surface of genus $g\geqslant 2$ with $k\geqslant 1$ marked points has $p$-periodic cohomology for each odd prime $p$ for which $\mathcal{N}_{g}^{k}$…

Algebraic Topology · Mathematics 2023-08-03 Nestor Colin , Rita Jiménez Rolland , Miguel A. Xicoténcatl

Let $N$ be a compact, connected, non-orientable surface of genus $\rho$ with $n$ boundary components, with $\rho \ge 5$ and $n \ge 0$, and let $\mathcal{M} (N)$ be the mapping class group of $N$. We show that, if $\mathcal{G}$ is a finite…

Geometric Topology · Mathematics 2017-08-02 Elmas Irmak , Luis Paris

This paper studies the problem of class-imbalanced graph classification, which aims at effectively classifying the graph categories in scenarios with imbalanced class distributions. While graph neural networks (GNNs) have achieved…

Machine Learning · Computer Science 2024-12-31 Wei Ju , Zhengyang Mao , Siyu Yi , Yifang Qin , Yiyang Gu , Zhiping Xiao , Jianhao Shen , Ziyue Qiao , Ming Zhang

Suppose X,Y are manifolds, f,g:X->Y are maps. The well-known Coincidence Problem studies the coincidence set C={x:f(x)=g(x)}. The number m=dimX-dimY is called the codimension of the problem. More general is the Preimage Problem. For a map…

Geometric Topology · Mathematics 2007-05-23 Peter Saveliev

It is given an efficient complete parametrization of wavelet matrices of rank $m$, genus $g+1$, and degree $g$, which are naturally identified with corresponding polynomial paraunitary matrix-functions. The parametrization depends on…

Classical Analysis and ODEs · Mathematics 2008-07-22 Lasha Ephremidze , Gigla Janashia , Edem Lagvilava

This self-contained paper is part of a series \cite{FF2,FF3} on actions by diffeomorphisms of infinite groups on compact manifolds. The two main results presented here are: 1) Any homomorphism of (almost any) mapping class group or…

Dynamical Systems · Mathematics 2016-09-07 Benson Farb , John Franks

A normal subgroup of the (extended) mapping class group of a surface is said to be geometric if its automorphism group is the mapping class group. We prove that in the case of the Cantor tree surface, every normal subgroup is geometric. We…

Group Theory · Mathematics 2020-02-18 Alan McLeay

For a compact surface $S = S_{g,n}$ with $3g + n \geq 4$, we introduce a family of unitary representations of the mapping class group Mod($S$) based on the space of measured foliations. For this family of representations, we show that none…

Geometric Topology · Mathematics 2021-03-02 Biao Ma

Symmetric nonnegative matrix factorization (NMF), a special but important class of the general NMF, is demonstrated to be useful for data analysis and in particular for various clustering tasks. Unfortunately, designing fast algorithms for…

Machine Learning · Computer Science 2018-11-15 Zhihui Zhu , Xiao Li , Kai Liu , Qiuwei Li

For an odd prime $p$, we determine the $p$-primary component of the Farrell cohomology of the pure mapping class groups of a non orientable surface of genus $p$ with $k\geqslant 1$ marked points. To do this, we classify conjugacy classes of…

Geometric Topology · Mathematics 2024-10-24 Nestor Colin

The Whitehead minimization problem consists in finding a minimum size element in the automorphic orbit of a word, a cyclic word or a finitely generated subgroup in a finite rank free group. We give the first fully polynomial algorithm to…

Group Theory · Mathematics 2008-01-06 Abdó Roig , Enric Ventura , Pascal Weil

A symmetric nonnegative matrix factorization algorithm based on self-paced learning was proposed to improve the clustering performance of the model. It could make the model better distinguish normal samples from abnormal samples in an…

Machine Learning · Computer Science 2024-10-22 Lei Wang , Liang Du , Peng Zhou , Peng Wu