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Diagram semigroups are interesting algebraic and combinatorial objects, several types of them originating from questions in computer science and in physics. Here we describe diagram semigroups in a general framework and extend our…

Group Theory · Mathematics 2015-02-27 James East , Attila Egri-Nagy , Andrew R. Francis , James D. Mitchell

We investigate the expressiveness of backward jumps in a framework of formalized sequential programming called program algebra. We show that - if expressiveness is measured in terms of the computability of partial Boolean functions - then…

Logic in Computer Science · Computer Science 2010-06-01 Jan A. Bergstra , Inge Bethke

In this paper, we discuss a method of constructing separable representations of the $C^*$-algebras associated to strongly connected row-finite $k$-graphs $\Lambda$. We begin by giving an alternative characterization of the…

Operator Algebras · Mathematics 2018-03-26 Carla Farsi , Elizabeth Gillaspy , Palle E. T. Jorgensen , Sooran Kang , Judith Packer

The category of admissible (in the appropriately modified sense of representation theory of totally disconnected groups) semi-linear representations of the automorphism group of an algebraically closed extension of infinite transcendence…

Representation Theory · Mathematics 2009-04-07 M. Rovinsky

We present a transductive learning algorithm that takes as input training examples from a distribution $P$ and arbitrary (unlabeled) test examples, possibly chosen by an adversary. This is unlike prior work that assumes that test examples…

Machine Learning · Computer Science 2020-10-01 Shafi Goldwasser , Adam Tauman Kalai , Yael Tauman Kalai , Omar Montasser

In this paper we introduce an inverse semigroup $\mathcal{S}(E,C)$ associated to a separated graph $(E,C)$ and describe its internal structure. In particular we show that it is strongly $E^*$-unitary and can be realized as a partial…

Operator Algebras · Mathematics 2025-06-03 Pere Ara , Alcides Buss , Ado Dalla Costa

The representation of graphs is commonly based on the adjacency matrix concept. This formulation is the foundation of most algebraic and computational approaches to graph processing. The advent of deep learning language models offers a wide…

Artificial Intelligence · Computer Science 2025-12-16 Ezequiel Lopez-Rubio

We introduce algebraic dynamical systems, which consist of an action of a right LCM semigroup by injective endomorphisms of a group. To each algebraic dynamical system we associate a C*-algebra and describe it as a semigroup C*-algebra. As…

Operator Algebras · Mathematics 2019-02-08 Nathan Brownlowe , Nadia S. Larsen , Nicolai Stammeier

The class of separable C*-algebras which can be written as inductive limits of continuous-trace C*-algebras with spectrum homeomorphic to a disjoint union of trees and trees with a point removed is classified by the Cuntz semigroup.

Operator Algebras · Mathematics 2010-04-05 Alin Ciuperca , George A. Elliott , Luis Santiago

Last years a number of papers were devoted to describing automorphisms of semigroups of endomorphisms of free finitely generated universal algebras of some varieties: groups, semigroups, associative commutative algebras, inverse semigroups,…

General Mathematics · Mathematics 2007-05-23 Grigori Zhitomirski

We wish to understand how irreducible representations of a group G behave when restricted to a subgroup G' (the branching problem). Our primary concern is with representations of reductive Lie groups, which involve both algebraic and…

Representation Theory · Mathematics 2016-08-31 Toshiyuki Kobayashi

In this paper we give an algebraic characterization of assemblies in terms of bands of groups. We also consider substructures and homomorphisms of assemblies. We give many examples and counterexamples.

Group Theory · Mathematics 2023-09-21 Ulderico Dardano , Bruno Dinis , Giuseppina Terzo

We obtain a kind of structure theorem for the automorphism group ${\rm Aut}{\cal A}$ of a unital C$^{*}$-algebra ${\cal A}$. According to it, ${\rm Aut}{\cal A}$ can be regarded as a subgroup of the semi-direct product of direct product…

Operator Algebras · Mathematics 2007-05-23 Katsunori Kawamura

Learning useful representations with little or no supervision is a key challenge in artificial intelligence. We provide an in-depth review of recent advances in representation learning with a focus on autoencoder-based models. To organize…

Machine Learning · Computer Science 2018-12-13 Michael Tschannen , Olivier Bachem , Mario Lucic

We introduce a class of algebras over a field $\mathbb{F}$ related to directed graphs in which all edges are labeled by nonzero elements of the field $\mathbb{F}$. If all labels are different from $1$, these algebras are axial algebras. We…

Commutative Algebra · Mathematics 2026-03-05 Hans Cuypers

Recent recommender system advancements have focused on developing sequence-based and graph-based approaches. Both approaches proved useful in modeling intricate relationships within behavioral data, leading to promising outcomes in…

Information Retrieval · Computer Science 2024-03-18 Vladimir Baikalov , Evgeny Frolov

We introduce a novel co-learning paradigm for manifolds naturally equipped with a group action, motivated by recent developments on learning a manifold from attached fibre bundle structures. We utilize a representation theoretic mechanism…

Machine Learning · Computer Science 2019-12-10 Yifeng Fan , Tingran Gao , Zhizhen Zhao

When a semigroup has a unary operation, it is possible to define two binary operations, namely, left and right division. In addition it is well known that groups can be defined in terms of those two divisions. The aim of this paper is to…

Group Theory · Mathematics 2012-10-01 Joao Araujo , Michael Kinyon

We examine two fundamental tasks associated with graph representation learning: link prediction and semi-supervised node classification. We present a novel autoencoder architecture capable of learning a joint representation of both local…

Machine Learning · Computer Science 2019-03-12 Phi Vu Tran

In many real-world scenarios, labeled data for a specific machine learning task is costly to obtain. Semi-supervised training methods make use of abundantly available unlabeled data and a smaller number of labeled examples. We propose a new…

Computer Vision and Pattern Recognition · Computer Science 2017-06-06 Philip Häusser , Alexander Mordvintsev , Daniel Cremers