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The notion of Poisson manifold with compatible pseudo-metric was introduced by the author in [1]. In this paper, we introduce a new class of Lie algebras which we call a pseudo-Rieamannian Lie algebras. The two notions are strongly related:…

Differential Geometry · Mathematics 2007-05-23 Mohamed Boucetta

In this paper, we introduce a novel generalization of the classical property of algebras known as "being alternative," which we term "partially alternative." This new concept broadens the scope of alternative algebras, offering a fresh…

Rings and Algebras · Mathematics 2025-05-14 Tianran Hua , Ekaterina Napedenina , Marina Tvalavadze

The set theory relations \in, \backslash, \Delta, \cap, and \cup have corollaries in subspace relations. Geometric Algebra is introduced as the ideal framework to explore these subspace operations. The relations \in, \backslash, and \Delta…

Rings and Algebras · Mathematics 2007-05-23 T. A. Bouma , L. Dorst , H. G. J. Pijls

We establish new results and introduce new methods in the theory of measurable orbit equivalence, using bounded cohomology of group representations. Our rigidity statements hold for a wide (uncountable) class of groups arising from negative…

Group Theory · Mathematics 2007-05-23 Nicolas Monod , Yehuda Shalom

A mathematical model of Subject behaviour choice is proposed. The background of the model is the concept of two preference relations determining Subject behaviour. These are an "internal" or subjective preference relation and an "external"…

Logic · Mathematics 2025-10-20 Valeriy K. Bulitko

The class of quasisymmetric mappings on the real axis was first introduced by A. Beurling and L. V. Ahlfors in 1956. In 1980 P. Tukia and J. V\"{a}is\"{a}l\"{a} considered these mappings between general metric spaces. In our paper we…

General Topology · Mathematics 2025-01-03 Evgeniy Petrov , Ruslan Salimov

In pregeometry a metric arises as a composite object at large distances. We investigate if its signature, which distinguishes between time and space, could be a result of the dynamics rather than being built in already in the formulation of…

General Relativity and Quantum Cosmology · Physics 2022-06-29 C. Wetterich

We study the problem of supervised learning a metric space under discriminative constraints. Given a universe $X$ and sets ${\cal S}, {\cal D}\subset {X \choose 2}$ of similar and dissimilar pairs, we seek to find a mapping $f:X\to Y$, into…

Computational Geometry · Computer Science 2019-03-20 Diego Ihara Centurion , Neshat Mohammadi , Anastasios Sidiropoulos

We lay down the foundations of a theory of parametrised functor calculus, generalising parts of the functor calculus of Goodwillie. We introduce the notion of excisable posets and develop a theory of excisive approximations in this context.…

Algebraic Topology · Mathematics 2024-10-30 Kaif Hilman , Sil Linskens

Following our approach to metric Lie algebras developed in math.DG/0312243 we propose a way of understanding pseudo-Riemannian symmetric spaces which are not semi-simple. We introduce cohomology sets (called quadratic cohomology) associated…

Differential Geometry · Mathematics 2007-05-23 Ines Kath , Martin Olbrich

We continue our efforts to understand, within the framework of the quantum mechanics of the universe as a whole, the quasiclassical realm of familiar experience as a feature emergent from the Hamiltonian of the elementary particles and the…

Quantum Physics · Physics 2019-05-16 Murray Gell-Mann , James Hartle

Thurston introduced in his seminal work an asymmetric metric on Teichm\"uller space by the ratio of simple closed curve length. In this paper, we generalize the idea and define an asymmetric metric on the space of unit-area flat metrics…

Geometric Topology · Mathematics 2025-10-21 Jiajun Shi

This paper investigates the problem of finding a preference relation on a set of acts from the knowledge of an ordering on events (subsets of states of the world) describing the decision-maker (DM)s uncertainty and an ordering of…

Artificial Intelligence · Computer Science 2013-02-08 Didier Dubois , Helene Fargier , Henri Prade

A generalization of metric space is presented which is shown to admit a theory strongly related to that of ordinary metric spaces. To avoid the topological effects related to dropping any of the axioms of metric space, first a new, and…

Metric Geometry · Mathematics 2012-01-20 Ittay Weiss

In physics, two systems that radically differ at short scales can exhibit strikingly similar macroscopic behaviour: they are part of the same long-distance universality class. Here we apply this viewpoint to geometry and initiate a program…

High Energy Physics - Theory · Physics 2023-11-22 Adam R. Brown , Michael H. Freedman , Henry W. Lin , Leonard Susskind

Despite advances in representation learning, high-dimensional classification remains challenging in low-sample-size regimes, where the dominant signal may vary across applications and labeled data are often limited. We propose a…

Methodology · Statistics 2026-05-18 Xiangbo Mo , Hao Chen

We consider a preference learning setting where every participant chooses an ordered list of $k$ most preferred items among a displayed set of candidates. (The set can be different for every participant.) We identify a distance-based…

Machine Learning · Computer Science 2023-01-24 Yifan Feng , Yuxuan Tang

Persistence modules are representations of products of totally ordered sets in the category of vector spaces. They appear naturally in the representation theory of algebras, but in recent years they have also found applications in other…

Algebraic Topology · Mathematics 2024-11-04 Steve Oudot

We consider decomposition spaces $\R^3/G$ that are manifold factors and admit defining sequences consisting of cubes-with-handles. Metrics on $\R^3/G$ constructed via modular embeddings into Euclidean spaces promote the controlled topology…

Metric Geometry · Mathematics 2013-08-08 Pekka Pankka , Jang-Mei Wu

Deep Learning performs well when training data densely covers the experience space. For complex problems this makes data collection prohibitively expensive. We propose to intelligently select samples when constructing data sets in order to…

Computer Vision and Pattern Recognition · Computer Science 2020-04-01 Mark Philip Philipsen , Thomas Baltzer Moeslund