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Stacks have become a prevalent tool in studying problems with connections to String Theory, hence we see a need to develop a theory of supersymmetric stacks proper. We first define derived stacks on $\mathbb{Z}_2$-bi-graded k-modules…

Algebraic Geometry · Mathematics 2021-02-02 Renaud Gauthier

In the framework of Abstract Differential Geometry, we show that to a given principal sheaf and a representation of its stuctural sheaf in $A^n$, where A is a sheaf of associative, commutative, unital algebras (over R or C), we associate a…

Differential Geometry · Mathematics 2013-05-29 E. Vassiliou

It is well known that (stochastic) gradient descent has an implicit bias towards flat minima. In deep neural network training, this mechanism serves to screen out minima. However, the precise effect that this has on the trained network is…

Machine Learning · Computer Science 2020-08-11 Rotem Mulayoff , Tomer Michaeli

The paper looks at a scaled variant of the stochastic gradient descent algorithm for the matrix completion problem. Specifically, we propose a novel matrix-scaling of the partial derivatives that acts as an efficient preconditioning for the…

Machine Learning · Computer Science 2016-10-06 Bamdev Mishra , Rodolphe Sepulchre

We investigate smooth approximations of functions, with prescribed gradient behavior on a distinguished stratified subset of the domain. As an application, we outline how our results yield important consequences for a recently introduced…

Classical Analysis and ODEs · Mathematics 2015-07-21 D. Drusvyatskiy , M. Larsson

We establish theoretical recovery guarantees of a family of Riemannian optimization algorithms for low rank matrix recovery, which is about recovering an $m\times n$ rank $r$ matrix from $p < mn$ number of linear measurements. The…

Numerical Analysis · Mathematics 2016-04-12 Ke Wei , Jian-Feng Cai , Tony F. Chan , Shingyu Leung

We show that the categorical action of the shifted $q=0$ affine algebra can be used to construct semiorthogonal decomposition on the weight categories. In particular, this construction recovers Kapranov's exceptional collection when the…

Representation Theory · Mathematics 2023-01-02 You-Hung Hsu

We develop the theory of ind-coherent sheaves on schemes and stacks. The category of ind-coherent sheaves is closely related, but inequivalent, to the category of quasi-coherent sheaves, and the difference becomes crucial for the…

Algebraic Geometry · Mathematics 2012-09-25 Dennis Gaitsgory

Multigraded linear series generalize the classical morphism to the linear series of a basepoint-free line bundle on a scheme. We investigate the collection of the natural cornering morphisms into elementary bigraded linear series obtained…

Algebraic Geometry · Mathematics 2026-05-27 Ádám Gyenge , Balázs Szendrői

We prove that the dg category of perfect complexes on a smooth, proper Deligne-Mumford stack over a field of characteristic zero is geometric in the sense of Orlov, and in particular smooth and proper. On the level of triangulated…

Algebraic Geometry · Mathematics 2018-08-14 Daniel Bergh , Valery A. Lunts , Olaf M. Schnürer

We introduce a new moduli stack, called the Serre stable moduli stack, which corresponds to studying families of point objects in an abelian category with a Serre functor. This allows us in particular, to re-interpret the classical derived…

Representation Theory · Mathematics 2015-07-24 Daniel Chan , Boris Lerner

The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated shifts of a smooth and rapidly decaying function on a uniform grid to scattered data quasi-interpolation. It is shown that high order…

Numerical Analysis · Mathematics 2007-05-23 F. Lanzara , V. Maz'ya , G. Schmidt

For any locally free coherent sheaf on a fixed smooth projective curve, we study the class, in the Grothendieck ring of varieties, of the Quot scheme that parametrizes zero-dimensional quotients of the sheaf. We prove that this class…

Algebraic Geometry · Mathematics 2019-07-02 Massimo Bagnarol , Barbara Fantechi , Fabio Perroni

In this paper, we study a class of discrete Morse functions, coming from Discrete Morse Theory, that are equivalent to a class of simplicial stacks, coming from Mathematical Morphology. We show that, as in Discrete Morse Theory, we can see…

Discrete Mathematics · Computer Science 2022-10-06 Nicolas Boutry , Gilles Bertrand , Laurent Najman

We construct a sheaf theoretic and derived geometric machinery to study nonlinear partial differential equations and their singular supports. We establish a notion of derived microlocalization for solution spaces of non-linear equations and…

Algebraic Geometry · Mathematics 2024-06-18 Jacob Kryczka , Artan Sheshmani , Shing-Tung Yau

In this paper we focus on the linear functionals defining an approximate version of the gradient of a function. These functionals are often used when dealing with optimization problems where the computation of the gradient of the objective…

Optimization and Control · Mathematics 2021-05-21 Marco Boresta , Tommaso Colombo , Alberto De Santis , Stefano Lucidi

A reduced divisor on a nonsingular variety defines the sheaf of logarithmic 1-forms. We introduce a certain coherent sheaf whose double dual coincides with this sheaf. It has some nice properties, for example, the residue exact sequence…

Algebraic Geometry · Mathematics 2007-05-23 Igor V. Dolgachev

Given a stratified variety X with strata satisfying a cohomological parity-vanishing condition, we define and show the uniqueness of "parity sheaves", which are objects in the constructible derived category of sheaves with coefficients in…

Representation Theory · Mathematics 2016-03-31 Daniel Juteau , Carl Mautner , Geordie Williamson

Networks are a useful representation for data on connections between units of interests, but the observed connections are often noisy and/or include missing values. One common approach to network analysis is to treat the network as a…

Methodology · Statistics 2017-05-22 Yun-Jhong Wu , Elizaveta Levina , Ji Zhu

Motivated by a wide variety of applications, ranging from stochastic optimization to dimension reduction through variable selection, the problem of estimating gradients accurately is of crucial importance in statistics and learning theory.…

Machine Learning · Computer Science 2020-06-29 Guillaume Ausset , Stephan Clémençon , François Portier