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One of the fundamental tasks of science is to find explainable relationships between observed phenomena. One approach to this task that has received attention in recent years is based on probabilistic graphical modelling with sparsity…

Machine Learning · Statistics 2014-04-16 Peter Orchard , Felix Agakov , Amos Storkey

The classification of Riemannian manifolds by the holonomy group of their Levi-Civita connection picks out many interesting classes of structures, several of which are solutions to the Einstein equations. The classification has two parts.…

Differential Geometry · Mathematics 2007-05-23 Richard Cleyton , Andrew Swann

In this paper we study singular integrals on small (that is, measure zero and lower than full dimensional) subsets of metric groups. The main examples of the groups we have in mind are Euclidean spaces and Heisenberg groups. In addition to…

Analysis of PDEs · Mathematics 2016-10-17 Vasilis Chousionis , Pertti Mattila

We study the exponential map of connected symmetric spaces and characterize, in terms of midpoints and of infinitesimal conditions, when it is a diffeomorphism, generalizing the Dixmier-Saito theorem for solvable Lie groups. We then give a…

Differential Geometry · Mathematics 2015-07-27 Yannick Voglaire

We consider rigid supersymmetric theories in four-dimensional Riemannian spin manifolds. We build the Lagrangian directly in Euclidean signature from the outset, keeping track of potential boundary terms. We reformulate the conditions for…

High Energy Physics - Theory · Physics 2015-06-04 Henning Samtleben , Dimitrios Tsimpis

Introductory lectures on higher-spin gauge theory given at 7 Aegean workshop on non-Einstein theories of gravity. The emphasis is on qualitative features of the higher-spin gauge theory and peculiarities of its space-time interpretation. In…

High Energy Physics - Theory · Physics 2015-06-19 M. A. Vasiliev

Solution and analysis of mathematical programming problems may be simplified when these problems are symmetric under appropriate linear transformations. In particular, a knowledge of the symmetries may help reduce the problem dimension, cut…

Optimization and Control · Mathematics 2020-10-13 A. V. Eremeev , A. S. Yurkov

In this paper the Gaussian integral is proven using contour integration on $\frac{1}{e^{x^2}+1}$ and linking it using a limit to said Gaussian integral. The limit is alsorelated to the Riemann Zeta function using a few manipulations. This…

Complex Variables · Mathematics 2024-02-15 Bastien Jean Quemener

In this work we compute the families of classical Hamiltonians in two degrees of freedom in which the Normal Variational Equation around an invariant plane falls in Schroedinger type with polynomial or trigonometrical potential. We analyze…

Mathematical Physics · Physics 2007-05-23 Primitivo Acosta-Humanez , David Blazquez-Sanz

This is a brief review of our recent work attempted at a generalization of the Grassmann algebra to the paragrassmann ones. The main aim is constructing an algebraic basis for representing `fractional' symmetries appearing in $2D$…

High Energy Physics - Theory · Physics 2007-05-23 A. T. Filippov , A. B. Kurdikov

Using the Magri method one defines an involutive family of Hamiltonians on Banach Lie-Poisson space iR+UL_res^1 (which contains the restricted Grassmannian as a symplectic leaf) and on its complexification C+L_res^1. The hierarchy of…

Mathematical Physics · Physics 2010-09-01 Tomasz Golinski , Anatol Odzijewicz

Popular deterministic approximations of posterior distributions from, e.g. the Laplace method, variational Bayes and expectation-propagation, generally rely on symmetric approximating families, often taken to be Gaussian. This choice…

Methodology · Statistics 2026-01-19 Francesco Pozza , Daniele Durante , Botond Szabo

The phase space of a compact, irreducible, simply connected, Riemannian symmetric space admits a natural family of K\"ahler polarizations parametrized by the upper half plane $S$. Using this family, geometric quantization, including the…

Mathematical Physics · Physics 2017-06-28 Róbert Szőke

The 2-rank of a compact Lie group $G$ is the maximal possible rank of the elementary 2-subgroup ${\mathbb Z}_{2}\times... {\mathbb Z}_{2}$ of $G$. The study of 2-ranks (and $p$-rank for any prime $p$) of compact Lie groups was initiated in…

Group Theory · Mathematics 2013-07-09 Bang-Yen Chen

Methods for inference and simulation of linearly constrained Gaussian Markov Random Fields (GMRF) are computationally prohibitive when the number of constraints is large. In some cases, such as for intrinsic GMRFs, they may even be…

Methodology · Statistics 2021-06-04 David Bolin , Jonas Wallin

Certain solvable extensions of $H$-type groups provide noncompact counterexamples to the so-called Lichnerowicz conjecture, which asserted that ``harmonic'' Riemannian spaces must be rank 1 symmetric spaces.

Differential Geometry · Mathematics 2009-09-25 Ewa Damek , Fulvio Ricci

We consider an ensemble of $2\times 2$ normal matrices with complex entries representing operators in the quantum mechanics of 2 - level parity-time reversal (PT) symmetric systems. The randomness of the ensemble is endowed by obtaining…

Mathematical Physics · Physics 2025-01-14 Stalin Abraham , A. Bhagwat , Sudhir Ranjan Jain

We establish theoretical recovery guarantees of a family of Riemannian optimization algorithms for low rank matrix recovery, which is about recovering an $m\times n$ rank $r$ matrix from $p < mn$ number of linear measurements. The…

Numerical Analysis · Mathematics 2016-04-12 Ke Wei , Jian-Feng Cai , Tony F. Chan , Shingyu Leung

This paper presents a novel estimator for a non-standard restriction to both symmetry and low rank in the context of high dimensional cointegrated processes. Furthermore, we discuss rank estimation for high dimensional cointegrated…

Methodology · Statistics 2022-08-16 Jacob Stærk-Østergaard , Anders Rahbek , Susanne Ditlevsen

We introduce a novel relaxation of combinatorial discrepancy called Gaussian discrepancy, whereby binary signings are replaced with correlated standard Gaussian random variables. This relaxation effectively reformulates an optimization…

Discrete Mathematics · Computer Science 2022-08-11 Sinho Chewi , Patrik Gerber , Philippe Rigollet , Paxton Turner
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