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Representing data in hyperbolic space can effectively capture latent hierarchical relationships. With the goal of enabling accurate classification of points in hyperbolic space while respecting their hyperbolic geometry, we introduce…

Machine Learning · Computer Science 2018-06-04 Hyunghoon Cho , Benjamin DeMeo , Jian Peng , Bonnie Berger

We construct a nonuniform lattice and an infinite family of uniform lattices in the automorphism group of a hyperbolic building with all links a fixed finite building of rank 2 associated to a Chevalley group. We use complexes of groups and…

Group Theory · Mathematics 2007-05-23 Anne Thomas

We consider the problem of multi-label classification where the labels lie in a hierarchy. However, unlike most existing works in hierarchical multi-label classification, we do not assume that the label-hierarchy is known. Encouraged by the…

Machine Learning · Computer Science 2021-01-14 Soumya Chatterjee , Ayush Maheshwari , Ganesh Ramakrishnan , Saketha Nath Jagaralpudi

Hyperbolic spaces, which have the capacity to embed tree structures without distortion owing to their exponential volume growth, have recently been applied to machine learning to better capture the hierarchical nature of data. In this…

Machine Learning · Computer Science 2021-03-18 Ryohei Shimizu , Yusuke Mukuta , Tatsuya Harada

We provide a diagrammatic criterion for semi-adequate links to be hyperbolic. We also give a conjectural description of the satellite structures of semi-adequate links. One application of our result is that the closures of sufficiently…

Geometric Topology · Mathematics 2016-02-12 David Futer , Efstratia Kalfagianni , Jessica S. Purcell

Hierarchical Topic Models (HTMs) are useful for discovering topic hierarchies in a collection of documents. However, traditional HTMs often produce hierarchies where lowerlevel topics are unrelated and not specific enough to their…

Information Retrieval · Computer Science 2023-05-17 Simra Shahid , Tanay Anand , Nikitha Srikanth , Sumit Bhatia , Balaji Krishnamurthy , Nikaash Puri

Many high-dimensional and large-volume data sets of practical relevance have hierarchical structures induced by trees, graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks low-dimensional…

Machine Learning · Computer Science 2021-09-16 Eli Chien , Chao Pan , Puoya Tabaghi , Olgica Milenkovic

We study the boundaries of relatively hyperbolic HHGs. Using the simplicial structure on the hierarchically hyperbolic boundary, we characterize both relative hyperbolicity and being thick of order 1 among HHGs. In the case of relatively…

Group Theory · Mathematics 2023-05-29 Carolyn Abbott , Jason Behrstock , Jacob Russell

An interacting lattice model describing the subspace spanned by a set of strongly-correlated bands is rigorously coupled to density functional theory to enable ab initio calculations of geometric and topological material properties. The…

Strongly Correlated Electrons · Physics 2019-03-26 Ryan Requist , E. K. U. Gross

In this paper we give new requirements that a tree of $\delta$-hyperbolic spaces has to satisfy in order to be $\delta$-hyperbolic itself. As an application, we give a simple proof that limit groups are relatively hyperbolic.

Group Theory · Mathematics 2007-05-23 Emina Alibegovic

Starting from the (apparently) elementary problem of deciding how many different topological spaces can be obtained by gluing together in pairs the faces of an octahedron, we will describe the central role played by hyperbolic geometry…

Geometric Topology · Mathematics 2011-01-18 Carlo Petronio , Damian Heard , Ekaterina Pervova

How can we represent hierarchical information present in large type inventories for entity typing? We study the ability of hyperbolic embeddings to capture hierarchical relations between mentions in context and their target types in a…

Computation and Language · Computer Science 2019-06-07 Federico López , Benjamin Heinzerling , Michael Strube

Learning the representation of data with hierarchical structures in the hyperbolic space attracts increasing attention in recent years. Due to the constant negative curvature, the hyperbolic space resembles tree metrics and captures the…

Machine Learning · Computer Science 2022-02-21 Huiru Xiao , Caigao Jiang , Yangqiu Song , James Zhang , Junwu Xiong

We use a combinatorial approximation of the hyperbolic plane to investigate properties of hyperbolic geometry such as exponential growth of perimeter and area of disks, and the linear isoperimetric inequality. This calculations give a…

Geometric Topology · Mathematics 2024-04-09 MurphyKate Montee

We start to develop the quantization formalism in a hyperbolic Hilbert space. Generalizing Born's probability interpretation, we found that unitary transformations in such a Hilbert space represent a new class of transformations of…

Quantum Physics · Physics 2007-05-23 Andrei Khrennikov

We introduce a new class of discrete conformal structures on surfaces with boundary, which have nice interpolations in 3-dimensional hyperbolic geometry. Then we prove the global rigidity of the new discrete conformal structures using…

Geometric Topology · Mathematics 2022-08-11 Xu Xu

We study the combinatorics of hyperplane arrangements over arbitrary fields. Specifically, we determine in which situation an arrangement and its reduction modulo a prime number have isomorphic lattices via the use of minimal strong…

Combinatorics · Mathematics 2021-04-05 Elisa Palezzato , Michele Torielli

We introduce a new combinatorial structure: the superselector. We show that superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel…

Data Structures and Algorithms · Computer Science 2010-10-07 Ferdinando Cicalese , Ugo Vaccaro

We explain how to construct certain potential functions for the hyperbolic structures of a knot complement, which are closely related to the analytic functions on the deformation space of hyperbolic structures.

Geometric Topology · Mathematics 2007-05-23 Yoshiyuki Yokota

Recently, there has been a surge of interest in representation learning in hyperbolic spaces, driven by their ability to represent hierarchical data with significantly fewer dimensions than standard Euclidean spaces. However, the viability…

Machine Learning · Computer Science 2022-11-02 Melanie Weber , Manzil Zaheer , Ankit Singh Rawat , Aditya Menon , Sanjiv Kumar