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This is a survey paper on derived symplectic geometry, that will appear as a chapter contribution to the book "New Spaces for Mathematics and Physics", edited by Mathieu Anel and Gabriel Catren. Our goal is to explain how derived stacks can…

Symplectic Geometry · Mathematics 2021-04-08 Damien Calaque

Stochastic gradient descent (SGD) is a promising numerical method for solving large-scale inverse problems. However, its theoretical properties remain largely underexplored in the lens of classical regularization theory. In this note, we…

Numerical Analysis · Mathematics 2020-07-22 Tim Jahn , Bangti Jin

In this work, we present a new approach to analyze the gradient flow for a positive semi-definite matrix denoising problem in an extensive-rank and high-dimensional regime. We use recent linear pencil techniques of random matrix theory to…

Machine Learning · Statistics 2023-03-17 Antoine Bodin , Nicolas Macris

These are expended notes of my talk at the summer institute in algebraic geometry (Seattle, July-August 2005), whose main purpose is to present a global overview on the theory of higher and derived stacks. This text is far from being…

Algebraic Geometry · Mathematics 2007-05-23 B. Toen

A differential version of the classical Weil descent is established in all characteristics. It yields a theory of differential restriction of scalars for differential varieties over finite differential field extensions. This theory is then…

Algebraic Geometry · Mathematics 2018-07-31 Omar León Sánchez , Marcus Tressl

The elementary theory of bivariate linear Diophantine equations over polynomial rings is used to construct causal lifting factorizations (elementary matrix decompositions) for causal two-channel FIR perfect reconstruction transfer matrices…

Information Theory · Computer Science 2024-12-03 Christopher M. Brislawn

In the context of linear inverse problems, we propose and study a general iterative regularization method allowing to consider large classes of regularizers and data-fit terms. The algorithm we propose is based on a primal-dual diagonal…

Optimization and Control · Mathematics 2017-08-04 Guillaume Garrigos , Lorenzo Rosasco , Silvia Villa

We propose a novel approach for studying rooted trees by using functions that we will call descent functions. We provide a construction method for rooted trees that allows to study their properties through the use of descent functions.…

Number Theory · Mathematics 2014-09-23 Marco Abrate , Stefano Barbero , Umberto Cerruti , Nadir Murru

We develop a formalism of cohomological descent encoding adelic points and obstructions to local-global principle on algebraic stacks. As an application, by constructing new obstructions using the formalism, we obtain some comparison…

Algebraic Geometry · Mathematics 2026-03-25 Chang Lv

We develop the theory of linear evolution equations associated with the adjacency matrix of a graph, focusing in particular on infinite graphs of two kinds: uniformly locally finite graphs as well as locally finite line graphs. We discuss…

Dynamical Systems · Mathematics 2018-07-26 Delio Mugnolo

In this article we show that a general notion of descent in coarse geometry can be applied to the study of injectivity of the $KH$-assembly map. We also show that the coarse assembly map is injective in general for finite coarse…

K-Theory and Homology · Mathematics 2016-11-26 Paul D. Mitchener

This paper provides a unifying view of a wide range of problems of interest in machine learning by framing them as the minimization of functionals defined on the space of probability measures. In particular, we show that generative…

Machine Learning · Computer Science 2019-05-21 Casey Chu , Jose Blanchet , Peter Glynn

In this paper, we study the gradient descent-ascent method for convex-concave saddle-point problems. We derive a new non-asymptotic global convergence rate in terms of distance to the solution set by using the semidefinite programming…

Optimization and Control · Mathematics 2022-09-19 Moslem Zamani , Hadi Abbaszadehpeivasti , Etienne de Klerk

We rewrite Arthur's asymptotic formula for weighted orbital integrals on real groups with the aid of a residue calculus and extend the resulting formula to the Schwartz space. Then we extract the available information about the coefficients…

Representation Theory · Mathematics 2008-09-01 Werner Hoffmann

Stochastic gradient methods enable learning probabilistic models from large amounts of data. While large step-sizes (learning rates) have shown to be best for least-squares (e.g., Gaussian noise) once combined with parameter averaging,…

Machine Learning · Statistics 2018-11-22 Dmitry Babichev , Francis Bach

This paper initiates a novel research direction in the theory of Diophantine equations: define an appropriate version of the equation's size, order all polynomial Diophantine equations starting from the smallest ones, and then solve the…

General Mathematics · Mathematics 2022-04-15 Bogdan Grechuk

Accurate quantum tomography is a vital tool in both fundamental and applied quantum science. It is a task that involves processing a noisy measurement record in order to construct a reliable estimate of an unknown quantum state, and is…

Quantum Physics · Physics 2017-01-02 Eliot Bolduc , George Knee , Erik Gauger , Jonathan Leach

In this short position paper we briefly review the development history of automated inductive theorem proving and computer-assisted mathematical induction. We think that the current low expectations on progress in this field result from a…

Artificial Intelligence · Computer Science 2013-09-17 Claus-Peter Wirth

We prove the excision theorem for the $K$-theory of perfect complexes on Deligne-Mumford stacks. This is then used to study the Nisnevich site of such stacks. We prove the Nisnevich descent for the $K$-theory of perfect complexes. We also…

Algebraic Geometry · Mathematics 2010-05-07 Amalendu Krishna , Paul-Arne Ostvaer

Accelerated gradient descent iterations are widely used in optimization. It is known that, in the continuous-time limit, these iterations converge to a second-order differential equation which we refer to as the accelerated gradient flow.…

Optimization and Control · Mathematics 2020-06-16 Mohammad Farazmand