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The identifiability problem arises naturally in a number of contexts in mathematics and computer science. Specific instances include local or global rigidity of graphs and unique completability of partially-filled tensors subject to rank…

Metric Geometry · Mathematics 2024-01-24 James Cruickshank , Fatemeh Mohammadi , Anthony Nixon , Shin-ichi Tanigawa

The Small Set Expansion Hypothesis (SSEH) is a conjecture which roughly states that it is NP-hard to distinguish between a graph with a small subset of vertices whose edge expansion is almost zero and one in which all small subsets of…

Computational Complexity · Computer Science 2017-05-11 Pasin Manurangsi

For a positive integer $k$ and a graph $H$ on $k$ vertices, we are interested in the inducibility of $H$, denoted $\mathrm{ind}(H)$, which is defined as the maximum possible probability that choosing $k$ vertices uniformly at random from a…

Combinatorics · Mathematics 2024-11-27 Richard Ueltzen

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

We introduce the problem Partial VC Dimension that asks, given a hypergraph $H=(X,E)$ and integers $k$ and $\ell$, whether one can select a set $C\subseteq X$ of $k$ vertices of $H$ such that the set $\{e\cap C, e\in E\}$ of distinct…

Data Structures and Algorithms · Computer Science 2019-05-29 Cristina Bazgan , Florent Foucaud , Florian Sikora

Robots are often required to localize in environments with unknown object classes and semantic ambiguity. However, when performing global localization using semantic objects, high semantic ambiguity intensifies object misclassification and…

Robotics · Computer Science 2025-12-16 Gihyeon Lee , Jungwoo Lee , Juwon Kim , Young-Sik Shin , Younggun Cho

Knowledge graphs have emerged as fundamental structures for representing complex relational data across scientific and enterprise domains. However, existing embedding methods face critical limitations when modeling diverse relationship…

Artificial Intelligence · Computer Science 2025-11-17 Jugal Gajjar , Kaustik Ranaware , Kamalasankari Subramaniakuppusamy , Vaibhav Gandhi

Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention…

Information Theory · Computer Science 2016-11-18 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

Clique-width is one of the most important parameters that describes structural complexity of a graph. Probably, only treewidth is more studied graph width parameter. In this paper we study how clique-width influences the complexity of the…

Data Structures and Algorithms · Computer Science 2020-03-11 Ivan Bliznets , Danil Sagunov

This article discusses random hypergraphs with varying hyperedge sizes, admitting large hyperedges with size tending to infinity, and heavy-tailed limiting hyperedge size distributions. The main result describes a threshold for the random…

Combinatorics · Mathematics 2024-06-11 Elmer Bergman , Lasse Leskelä

There are increasing evidences that quantum information theory has come to play a fundamental role in quantum gravity especially the holography. In this paper, we show some new potential connections between holography and quantum…

High Energy Physics - Theory · Physics 2020-08-10 Dong-Hui Du , Fu-Wen Shu , Kai-Xin Zhu

Feature hashing, also known as {\em the hashing trick}, introduced by Weinberger et al. (2009), is one of the key techniques used in scaling-up machine learning algorithms. Loosely speaking, feature hashing uses a random sparse projection…

Machine Learning · Computer Science 2018-05-23 Casper Benjamin Freksen , Lior Kamma , Kasper Green Larsen

Hierarchical clustering (HC) is an important data analysis technique in which the goal is to recursively partition a dataset into a tree-like structure while grouping together similar data points at each level of granularity. Unfortunately,…

Data Structures and Algorithms · Computer Science 2025-06-09 Vladimir Braverman , Jon C. Ergun , Chen Wang , Samson Zhou

Deep hashing enables image retrieval by end-to-end learning of deep representations and hash codes from training data with pairwise similarity information. Subject to the distribution skewness underlying the similarity information, most…

Computer Vision and Pattern Recognition · Computer Science 2018-09-06 Zhangjie Cao , Ziping Sun , Mingsheng Long , Jianmin Wang , Philip S. Yu

Entity alignment has always had significant uses within a multitude of diverse scientific fields. In particular, the concept of matching entities across networks has grown in significance in the world of social science as communicative…

Social and Information Networks · Computer Science 2020-04-21 James Flamino , Christopher Abriola , Ben Zimmerman , Zhongheng Li , Joel Douglas

Let $H$ be a $(k+1)$-uniform hypergraph which is nearly $D$-regular, such that any set of $i$ vertices is contained in at most $D_i$ edges of $H$ for each $i = 2, 3, \dots, k+1$. Influential results of Pippenger and of Frankl and R\"odl…

Combinatorics · Mathematics 2025-11-17 Stephen Gould , Tom Kelly

Consider the binomial model $G^{d+1}(n,p)$ of the random $(d+1)$-uniform hypergraph on $n$ vertices, where each edge is present, independently of one another, with probability $p:\mathbb{N}\to[0,1]$. We prove that, for all…

Combinatorics · Mathematics 2016-02-23 Nicolau C. Saldanha , Márcio Telles

For given integers $r$ and $\ell$ such that $2\leqslant\ell\leqslant r-1$, an $r$-uniform hypergraph $H$ is called a partial Steiner $(n,r,\ell)$-system, if every subset of size $\ell$ lies in at most one edge of $H$. In particular, partial…

Combinatorics · Mathematics 2022-04-12 Fang Tian

We study randomness properties of graphs and hypergraphs generated by simple hash functions. Several hashing applications can be analyzed by studying the structure of $d$-uniform random ($d$-partite) hypergraphs obtained from a set $S$ of…

Data Structures and Algorithms · Computer Science 2016-11-02 Martin Aumüller , Martin Dietzfelbinger , Philipp Woelfel

Let $G\sim G(n,p)$ be a (hidden) Erd\H{o}s-R\'enyi random graph with $p=(1+ \varepsilon)/n$ for some fixed constant $ \varepsilon >0$. Ferber, Krivelevich, Sudakov, and Vieira showed that to reveal a path of length…

Combinatorics · Mathematics 2024-09-05 Vesna Iršič , Julien Portier , Leo Versteegen