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In this paper, we present a new construction of simplicial complexes of subpolynomial degree with arbitrarily good local spectral expansion. Previously, the only known high-dimensional expanders (HDXs) with arbitrarily good expansion and…

Combinatorics · Mathematics 2023-12-27 Louis Golowich

We extend nearness frames to posets representing bases and even subbases of $T_1$ spaces. This allows us to put a classic duality due to Wallman, between compact $T_1$ spaces and abstract simplicial complexes, into a general nearness…

General Topology · Mathematics 2019-02-22 Tristan Bice

High dimensional expanders is a vibrant emerging field of study. Nevertheless, the only known construction of bounded degree high dimensional expanders is based on Ramanujan complexes, whereas one dimensional bounded degree expanders are…

Combinatorics · Mathematics 2023-09-29 Tali Kaufman , Izhar Oppenheim

Trickle-down is a phenomenon in high-dimensional expanders with many important applications -- for example, it is a key ingredient in various constructions of high-dimensional expanders or the proof of rapid mixing for the basis exchange…

Probability · Mathematics 2024-07-24 Nima Anari , Frederic Koehler , Thuy-Duong Vuong

In this paper, we further explore the local-to-global approach for expansion of simplicial complexes that we call local spectral expansion. Specifically, we prove that local expansion in the links imply the global expansion phenomena of…

Combinatorics · Mathematics 2018-03-06 Izhar Oppenheim

We study high dimensional expansion beyond simplicial complexes (posets) and focus on $q$-complexes which are complexes whose basic building blocks are linear spaces. We show that the complete $q$-complex (consists of all subspaces of a…

Combinatorics · Mathematics 2024-01-24 Ran Tessler , Elad Tzalik

We initiate the study of Boolean function analysis on high-dimensional expanders. We give a random-walk based definition of high-dimensional expansion, which coincides with the earlier definition in terms of two-sided link expanders. Using…

Computational Complexity · Computer Science 2024-01-18 Yotam Dikstein , Irit Dinur , Yuval Filmus , Prahladh Harsha

In the recent past, nested structures in Riemannian manifolds has been studied in the context of dimensionality reduction as an alternative to the popular principal geodesic analysis (PGA) technique, for example, the principal nested…

Computer Vision and Pattern Recognition · Computer Science 2022-03-02 Chun-Hao Yang , Baba C. Vemuri

One of the most important properties of high dimensional expanders is that high dimensional random walks converge rapidly. This property has proven to be extremely useful in variety of fields in the theory of computer science from agreement…

Combinatorics · Mathematics 2023-10-02 Roy Gotlib , Tali Kaufman

This paper proposes a generalized framework with joint normalization which learns lower-dimensional subspaces with maximum discriminative power by making use of the Riemannian geometry. In particular, we model the similarity/dissimilarity…

Computer Vision and Pattern Recognition · Computer Science 2017-11-20 Tianci Liu , Zelin Shi , Yunpeng Liu

Garland introduced a vanishing criterion for a characteristic zero cohomology group of a locally finite and locally connected simplicial complex. The criterion is based on the spectral gaps of the graph Laplacians of the links of faces and…

Combinatorics · Mathematics 2026-05-05 Eric Babson , Volkmar Welker

In this paper we further develop a Grassmannian technique used to prove results about very general hypersurfaces and present three applications. First, we provide a short proof of the Kobayashi Conjecture given previous results on the…

Algebraic Geometry · Mathematics 2018-06-08 Eric Riedl , David Yang

For any finite poset we define a generating polynomial counting upsets, downsets, and their intersection. We investigate the behaviour of this polynomial with respect to poset operations, show that it distinguishes series-parallel posets,…

Combinatorics · Mathematics 2025-11-20 Ian George , Karen Yeats

6-DoF pose estimation is an essential component of robotic manipulation pipelines. However, it usually suffers from a lack of generalization to new instances and object types. Most widely used methods learn to infer the object pose in a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Vaibhav Saxena , Kamal Rahimi Malekshan , Linh Tran , Yotto Koga

Recent work has shown that two-dimensional non-linear $\sigma$-models on group manifolds with Poisson-Lie symmetry can be understood within generalised geometry as exemplars of generalised parallelisable spaces. Here we extend this idea to…

High Energy Physics - Theory · Physics 2019-12-24 Saskia Demulder , Falk Hassler , Giacomo Piccinini , Daniel C. Thompson

3D human pose data collected in controlled laboratory settings present challenges for pose estimators that generalize across diverse scenarios. To address this, domain generalization is employed. Current methodologies in domain…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Qucheng Peng , Ce Zheng , Chen Chen

Generalized Feller theory provides an important analog to Feller theory beyond locally compact state spaces. This is very useful for solutions of certain stochastic partial differential equations, Markovian lifts of fractional processes, or…

Probability · Mathematics 2023-08-09 Christa Cuchiero , Tonio Möllmann , Josef Teichmann

We study the conditions under which N=(1,1) generalized sigma models support an extension to N=(2,2). The enhanced supersymmetry is related to the target space complex geometry. Concentrating on a simple situation, related to Poisson sigma…

High Energy Physics - Theory · Physics 2009-11-11 Andreas Bredthauer , Ulf Lindstrom , Jonas Persson

Random walks on bounded degree expander graphs have numerous applications, both in theoretical and practical computational problems. A key property of these walks is that they converge rapidly to their stationary distribution. In this work…

Computational Complexity · Computer Science 2016-09-15 Tali Kaufman , David Mass

This paper introduces a novel approach to improve robotic grasping in dynamic environments by integrating Gaussian Process Distance Fields (GPDF), SE(3) equivariant networks, and Riemannian Mixture Models. The aim is to enable robots to…

Robotics · Computer Science 2024-03-08 Ho Jin Choi , Nadia Figueroa
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