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We develop a new method for visualizing and refining the invariances of learned representations. Specifically, we test for a general form of invariance, linearization, in which the action of a transformation is confined to a low-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2020-07-28 Olivier J. Hénaff , Eero P. Simoncelli

In one dimension, the theory of the $G$-normal distribution is well-developed, and many results from the classical setting have a nonlinear counterpart. Significant challenges remain in multiple dimensions, and some of what has already been…

Probability · Mathematics 2014-12-04 Erhan Bayraktar , Alexander Munk

We introduce in the framework of the linear approximation of General relativity a natural distinction between General gauge transformations generated by any vector field and those Special ones for which this vector field is a gradient. This…

General Relativity and Quantum Cosmology · Physics 2007-06-23 Ll. Bel

The primary purpose of this note is to prove two recent conjectures concerning the $n$ body matrix that arose in recent papers of Escobar-Ruiz, Miller, and Turbiner on the classical and quantum $n$ body problem in $d$-dimensional space.…

Mathematical Physics · Physics 2019-04-23 Darij Grinberg , Peter J. Olver

We describe the variety of fixed points of a unipotent operator acting on the space of matrices. We compute the determinant and the rank of a generic (symmetric, or anti-symmetric) matrix in the fixed variety, yielding information about the…

Algebraic Geometry · Mathematics 2013-02-26 Mahir Bilen Can , Roger Howe , Michael Joyce

Theory of matrix factorizations is useful to study hypersurfaces in commutative algebra. To study noncommutative hypersurfaces, which are important objects of study in noncommutative algebraic geometry, we introduce a notion of…

Rings and Algebras · Mathematics 2021-08-05 Izuru Mori , Kenta Ueyama

In this paper, we show how general determinants may be viewed as generating functions of nonintersecting lattice paths, using the Lindstr\"om-Gessel-Viennot interpretation of semistandard Young tableaux and the Jacobi-Trudi identity…

Combinatorics · Mathematics 2010-10-20 Markus Fulmek

A novel general framework is proposed in this paper for dimension reduction in regression to fill the gap between linear and fully nonlinear dimension reduction. The main idea is to transform first each of the raw predictors monotonically,…

Methodology · Statistics 2014-01-03 Tao Wang , Xu Guo , Peirong Xu , Lixing Zhu

In this work, we make new developments in generic cotangent bundle geometries, depending on all phase-space variables. In particular, we will focus on the so-called generalized Hamilton spaces, discussing how the main ingredients of this…

Mathematical Physics · Physics 2024-07-29 J. J. Relancio , L. Santamaría-Sanz

Let F be a finite extension of Qp and G be GL(2,F). When V is the tensor product of three admissible, irreducible, finite dimensional representations of G, the space of G-invariant linear forms has dimension at most one. When a non zero…

Number Theory · Mathematics 2007-05-23 Louise Nyssen

An introductory overview of vector spaces, algebras, and linear geometries over an arbitrary commutative field is given. Quotient spaces are emphasized and used in constructing the exterior and the symmetric algebras of a vector space.…

History and Overview · Mathematics 2011-10-18 Richard A. Smith

By considering generalized logarithm and exponential functions used in nonextensive statistics, the four usual algebraic operators : addition, subtraction, product and division, are generalized. The properties of the generalized operators…

Mathematical Physics · Physics 2009-11-10 L. Nivanen , A. Le Mehaute , Q. A. Wang

Random correlation matrices are studied for both theoretical interestingness and importance for applications. The author of [6] is interested in their interpretation as covariance matrices of purely random signals, the authors of [16]…

Probability · Mathematics 2016-07-28 A. M. Hanea , G. F Nane

Integral transforms are invaluable mathematical tools to map functions into spaces where they are easier to characterize. We introduce the hyperdimensional transform as a new kind of integral transform. It converts square-integrable…

Machine Learning · Computer Science 2023-10-26 Pieter Dewulf , Michiel Stock , Bernard De Baets

The u-invariant of a field is the supremum of the dimensions of anisotropic quadratic forms over the field. We define corresponding u-invariants for hermitian and generalised quadratic forms over a division algebra with involution in…

Rings and Algebras · Mathematics 2017-05-23 Andrew Dolphin

There are various types of global and local spacetime invariant in general relativity. Here I focus on the local invariants obtainable from the curvature tensor and its derivatives. The number of such invariants at each order of…

General Relativity and Quantum Cosmology · Physics 2015-04-28 Malcolm A. H. MacCallum

Monotone operators, especially in the form of subdifferential operators, are of basic importance in optimization. It is well known since Minty, Rockafellar, and Bertsekas-Eckstein that in Hilbert space, monotone operators can be understood…

Functional Analysis · Mathematics 2008-10-22 Heinz H. Bauschke , Xianfu Wang , Liangjin Yao

The link between the nucleon generalized parton distributions and the non-diagonal one-body density matrix in momentum space is studied. Attention is focussed on the region where quark generalized parton distributions (GPD's) describe…

High Energy Physics - Phenomenology · Physics 2009-11-07 S. Boffi , B. Pasquini , M. Traini

4x4x3 absolutely nonsingular tensors are characterized by their determinant polynomial. Non-quivalence among absolutely nonsingular tensors with respect to a class of linear transformations, which do not chage the tensor rank,is studied. It…

Machine learning systems generally assume that the training and testing distributions are the same. To this end, a key requirement is to develop models that can generalize to unseen distributions. Domain generalization (DG), i.e.,…

Machine Learning · Computer Science 2022-05-25 Jindong Wang , Cuiling Lan , Chang Liu , Yidong Ouyang , Tao Qin , Wang Lu , Yiqiang Chen , Wenjun Zeng , Philip S. Yu