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We introduce a toy model, which represents a simplified version of the problem of the depinning transition in the limit of strong disorder. This toy model can be formulated as a simple renormalization transformation for the probability…

Statistical Mechanics · Physics 2015-06-18 Bernard Derrida , Martin Retaux

In this work, we introduce Y-Drop, a regularization method that biases the dropout algorithm towards dropping more important neurons with higher probability. The backbone of our approach is neuron conductance, an interpretable measure of…

Machine Learning · Computer Science 2024-09-17 Efthymios Georgiou , Georgios Paraskevopoulos , Alexandros Potamianos

Generative adversarial networks (GANs) are so complex that the existing learning theories do not provide a satisfactory explanation for why GANs have great success in practice. The same situation also remains largely open for deep neural…

Machine Learning · Computer Science 2022-02-15 Khoat Than , Nghia Vu

We consider diffusion on discrete measure spaces as encoded by Markovian semigroups arising from weighted graphs. We study whether the graph is uniquely determined if the diffusion is given up to order isomorphism. If the graph is recurrent…

Functional Analysis · Mathematics 2014-05-14 Matthias Keller , Daniel Lenz , Marcel Schmidt , Melchior Wirth

Factorizations over cones and their duals play central roles for many areas of mathematics and computer science. One of the reasons behind this is the ability to find a representation for various objects using a well-structured family of…

Optimization and Control · Mathematics 2025-02-18 Adam Brown , Kanstantsin Pashkovich , Levent Tunçel

We prove a variety of results describing the possible diagonals of tuples of commuting hermitian operators in type $II_1$ factors. These results are generalisations of the classical Schur-Horn theorem to the infinite dimensional,…

Operator Algebras · Mathematics 2017-05-17 Pedro Massey , Mohan Ravichandran

Understanding how the test risk scales with model complexity is a central question in machine learning. Classical theory is challenged by the learning curves observed for large over-parametrized deep networks. Capacity measures based on…

Machine Learning · Statistics 2025-10-22 Yichen Wang , Yudong Chen , Lorenzo Rosasco , Fanghui Liu

This paper is devoted to the online dominating set problem and its variants. We believe the paper represents the first systematic study of the effect of two limitations of online algorithms: making irrevocable decisions while not knowing…

Data Structures and Algorithms · Computer Science 2018-09-14 Joan Boyar , Stephan J. Eidenbenz , Lene M. Favrholdt , Michal Kotrbčík , Kim S. Larsen

We show that recent multivariate generalizations of the Araki-Lieb-Thirring inequality and the Golden-Thompson inequality [Sutter, Berta, and Tomamichel, Comm. Math. Phys. (2016)] for Schatten norms hold more generally for all unitarily…

Mathematical Physics · Physics 2017-12-12 Fumio Hiai , Robert Koenig , Marco Tomamichel

The classical matrix-tree theorem was discovered by G.~Kirchhoff in 1847. It relates the principal minor of the Laplace (nxn)-matrix to a particular sum of monomials indexed by the set of trees with n vertices. The aim of this paper is to…

Combinatorics · Mathematics 2016-12-14 Yurii Burman

We study a natural measurable selection problem for which the standard uniformisation theorems do not seem to apply directly, yet a Borel selector exists. More precisely, we consider families of finite dimensional functions that admit…

Logic · Mathematics 2026-03-23 Eugenio Clerico

In this paper, we study the parameterized complexity of a generalized domination problem called the [${\sigma}, {\rho}$] Dominating Set problem. This problem generalizes a large number of problems including the Minimum Dominating Set…

Computational Complexity · Computer Science 2022-11-10 Pradeesha Ashok , Rajath Rao , Avi Tomar

We generalize the result of (Witkowski, 2014) which binds orders of homogeneous, symmetric means $M,N,K \colon\mathbb{R}_+^2 \to \mathbb{R}_+$ of power growth that satisfy the invariance equation $K(M(x,y),N(x,y))=K(x,y)$ to the broader…

Classical Analysis and ODEs · Mathematics 2023-10-31 Paweł Pasteczka

The nonlinear concepts of mixed summable families and maps for the spaces that only non-void sets are developed. Several characterizations of the corresponding concepts are achieved and the proof for a general Pietsch Domination-type…

Functional Analysis · Mathematics 2021-07-13 Salam Adel Al-Bayati , Akram Al-Sabbagh , Manaf Adnan Saleh Saleh

Generalization is a central aspect of learning theory. Here, we propose a framework that explores an auxiliary task-dependent notion of generalization, and attempts to quantitatively answer the following question: given two sets of patterns…

Disordered Systems and Neural Networks · Physics 2020-01-08 Francesco Borra , Marco Cosentino Lagomarsino , Pietro Rotondo , Marco Gherardi

We generalize Exel's notion of partial group action to monoids. For partial monoid actions that can be defined by means of suitably well-behaved systems of generators and relations, we employ classical rewriting theory in order to describe…

General Topology · Mathematics 2007-05-23 Michael Megrelishvili , Lutz Schroeder

Max Noether's Theorem asserts that if $\ww$ is the dualizing sheaf of a nonsingular nonhyperelliptic projective curve then the natural morphisms $\text{Sym}^nH^0(\omega)\to H^0(\omega^n)$ are surjective for all $n\geq 1$. This is true for…

Algebraic Geometry · Mathematics 2009-08-18 Renato Vidal Martins

Let X be a product of Drinfeld modular curves over a general base ring A of odd characteristic. We classify those subvarieties of X which contain a Zariski-dense set of CM points. This is an analogue of the Andr\'e-Oort conjecture. As an…

Number Theory · Mathematics 2007-05-23 Florian Breuer

The first-order theory of MALL (multiplicative, additive linear logic) over only equalities is an interesting but weak logic since it cannot capture unbounded (infinite) behavior. Instead of accounting for unbounded behavior via the…

Logic in Computer Science · Computer Science 2010-12-02 David Baelde

Transformer networks have seen great success in natural language processing and machine vision, where task objectives such as next word prediction and image classification benefit from nuanced context sensitivity across high-dimensional…

Machine Learning · Computer Science 2022-12-13 Yuxuan Li , James L. McClelland
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