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We compute the topological complexity of Eilenberg-Mac Lane spaces associated to the group of automorphisms of a finitely generated free group which act by conjugation on a given basis, and to certain subgroups.

Algebraic Topology · Mathematics 2008-12-31 Daniel C. Cohen , Goderdzi Pruidze

Using each node's degree as a proxy for its importance, the topological hierarchy of a complex network is introduced and quantified. We propose a simple dynamical process used to construct networks which are either maximally or minimally…

Soft Condensed Matter · Physics 2008-06-24 Ala Trusina , Sergei Maslov , Petter Minnhagen , Kim Sneppen

We survey results on the formalization and independence of mathematical statements related to major open problems in computational complexity theory. Our primary focus is on recent findings concerning the (un)provability of complexity…

Computational Complexity · Computer Science 2025-04-08 Igor C. Oliveira

The notion of analyticity is studied in the context of hypercomplex numbers. A critical review of the problems arising from the conventional approach is given. We describe a local analyticity condition which yields the desired type of…

funct-an · Mathematics 2008-02-03 Stefano De Leo , Pietro Rotelli

We develop a notion of computability and complexity of functions over the reals, which seems to be very natural when one tries to determine just how "difficult" a certain function is. This notion can be viewed as an extension of both BSS…

Computational Complexity · Computer Science 2007-05-23 Mark Braverman

We perform topological data analysis on the internal states of convolutional deep neural networks to develop an understanding of the computations that they perform. We apply this understanding to modify the computations so as to (a) speed…

Machine Learning · Computer Science 2018-11-06 Gunnar Carlsson , Rickard Brüel Gabrielsson

We utilize classical facts from topology to show that the classification problem in machine learning is always solvable under very mild conditions. Furthermore, we show that a softmax classification network acts on an input topological…

Machine Learning · Computer Science 2021-06-22 Mustafa Hajij , Kyle Istvan

We seek random versions of some classical theorems on complex approximation by polynomials and rational functions, as well as investigate properties of random compact sets in connection to complex approximation.

Complex Variables · Mathematics 2017-09-26 Simon St-Amant , Jérémie Turcotte

We define the topological complexity sequence of a group as the sequence of topological complexities of its Milnor constructions. This sequence may be regarded as an intrinsic refinement of the topological complexity of a group and, unlike…

Algebraic Topology · Mathematics 2026-05-07 Daisuke Kishimoto , Yuki Minowa

We introduce a new setting, the category of $\omega$PAP spaces, for reasoning denotationally about expressive differentiable and probabilistic programming languages. Our semantics is general enough to assign meanings to most practical…

Programming Languages · Computer Science 2023-05-29 Mathieu Huot , Alexander K. Lew , Vikash K. Mansinghka , Sam Staton

We introduce and analyze a new geometric structure on topological surfaces generalizing the complex structure. To define this so called higher complex structure we use the punctual Hilbert scheme of the plane. The moduli space of higher…

Differential Geometry · Mathematics 2025-07-08 Vladimir V. Fock , Alexander Thomas

The notions of compactness and Hausdorff separation for generalized enriched categories allow us, as classically done for the category $\mathsf{Top}$ of topological spaces and continuous functions, to study $\textit{compactly generated…

Category Theory · Mathematics 2019-08-13 Willian Ribeiro

This paper establishes the separation of complexity classes $\mathbf{P}$ and $\mathbf{NP}$ through a novel homological algebraic approach grounded in category theory. We construct the computational category $\mathbf{Comp}$, embedding…

Computational Complexity · Computer Science 2025-12-22 Jian-Gang Tang

Relative to the large literature on upper bounds on complexity of convex optimization, lesser attention has been paid to the fundamental hardness of these problems. Given the extensive use of convex optimization in machine learning and…

Machine Learning · Statistics 2011-11-22 Alekh Agarwal , Peter L. Bartlett , Pradeep Ravikumar , Martin J. Wainwright

1) We introduce random discrete Morse theory as a computational scheme to measure the complicatedness of a triangulation. The idea is to try to quantify the frequence of discrete Morse matchings with a certain number of critical cells. Our…

Computational Geometry · Computer Science 2014-04-21 Bruno Benedetti , Frank H. Lutz

We consider approximation or recovery of functions based on a finite number of function evaluations. This is a well-studied problem in optimal recovery, machine learning, and numerical analysis in general, but many fundamental insights were…

Numerical Analysis · Mathematics 2026-04-07 David Krieg , Mario Ullrich

We investigate the topological aspects of some algebraic computation models, in particular the BSS-model. Our results can be seen as bounds on how different BSS-computability and computability in the sense of computable analysis can be. The…

Logic in Computer Science · Computer Science 2017-03-20 Eike Neumann , Arno Pauly

In these notes, uniform convergence on compacta is studied on the space of functions taking values in the set of finite Borel measures. Related limit theorems, including L\'evy's continuity theorem and functional limit theorems for…

Probability · Mathematics 2026-01-13 Takahiro Hasebe , Ikkei Hotta , Takuya Murayama

We set up a formalism of Maurer-Cartan moduli sets for L-infinity algebras and associated twistings based on the closed model category structure on formal differential graded algebras (a.k.a. differential graded coalgebras). Among other…

Algebraic Topology · Mathematics 2012-12-11 Andrey Lazarev

This is a chapter in the Encyclopedia of Robotics. It is devoted to the study of complexity of complete (or exact) algorithms for robot motion planning. The term ``complete'' indicates that an approach is guaranteed to find the correct…

Robotics · Computer Science 2020-03-31 Kiril Solovey