Publications related to Separation and Duality in Locally L0-Convex Modules

Correspondence functors and duality

A correspondence functor is a functor from the category of finite sets and correspondences to the category of k-modules, where k is a commutative ring. By means of a suitably defined duality, new correspondence functors are constructed, having remarkable p ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Given two jointly distributed random variables (X,Y), a functional representation of X is a random variable Z independent of Y, and a deterministic function g(⋅,⋅) such that X=g(Y,Z). The problem of finding a minimum entropy functional representation is kn ...

2023

Moments of the number of points in a bounded set for number field lattices

Maryna Viazovska, Nihar Prakash Gargava, Vlad Serban

We examine the moments of the number of lattice points in a fixed ball of volume

V

for lattices in Euclidean space which are modules over the ring of integers of a number field

K

. In particular, denoting by

ω_K

the number of roots of unity in

K

, we ...

arXiv2023

Localizing Unsynchronized Sensors With Unknown Sources

Ivan Dokmanic, Dalia Salem Hassan Fahmy El Badawy

We propose a method for sensor array self-localization using a set of sources at unknown locations. The sources produce signals whose times of arrival are registered at the sensors. We look at the general case where neither the emission times of the source ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

Stochastic distributed learning with gradient quantization and double-variance reduction

Sebastian Urban Stich, Konstantin Mishchenko

We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed to compress the model updates in orde ...

TAYLOR & FRANCIS LTD2022

Generic direct summands of tensor products for simple algebraic groups and quantum groups at roots of unity

Jonathan Gruber

Let G be either a simple linear algebraic group over an algebraically closed field of characteristic l>0 or a quantum group at an l-th root of unity. The category Rep(G) of finite-dimensional G-modules is non-semisimple. In this thesis, we develop new tech ...

EPFL2022

Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift

Mathieu Salzmann

In many situations, the data one has access to at test time follows a different distribution from the training data. Over the years, this problem has been tackled by closed-set domain adaptation techniques. Recently, open-set domain adaptation has emerged ...

IEEE COMPUTER SOC2022

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Volkan Cevher, Kimon Antonakopoulos, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi, Ali Kavis

We propose an adaptive variance-reduction method, called AdaSpider, for minimization of L-smooth, non-convex functions with a finite-sum structure. In essence, AdaSpider combines an AdaGrad-inspired [Duchi et al., 2011, McMahan & Streeter, 2010], but a fai ...

2022

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Erixhen Sula

Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

EPFL2021

Separation and Duality in Locally L0-Convex Modules

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Correspondence functors and duality

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Moments of the number of points in a bounded set for number field lattices

Localizing Unsynchronized Sensors With Unknown Sources

A Functional Perspective on Information Measures

Stochastic distributed learning with gradient quantization and double-variance reduction

Generic direct summands of tensor products for simple algebraic groups and quantum groups at roots of unity

Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Moments of the number of points in a bounded set for number field lattices

Correspondence functors and duality

Generic direct summands of tensor products for simple algebraic groups and quantum groups at roots of unity

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Localizing Unsynchronized Sensors With Unknown Sources

A Functional Perspective on Information Measures

Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Stochastic distributed learning with gradient quantization and double-variance reduction