Publications associées à Vecteur contravariant, covariant et covecteur

Dynamical Low-Rank Approximation for Stochastic Differential Equations

Fabio Nobile, Yoshihito Kazashi, Fabio Zoccolan

In this paper, we set the mathematical foundations of the Dynamical Low-Rank Approximation (DLRA) method for stochastic differential equations (SDEs). DLRA aims at approximating the solution as a linear combination of a small number of basis vectors with r ...

American Mathematical Society (AMS)2024

Covariant formulation of relativistic mechanics

Miguel Alexandre Ribeiro Correia

Accretion disks surrounding compact objects, and other environmental factors, deviate satellites from geodetic motion. Unfortunately, setting up the equations of motion for such relativistic trajectories is not as simple as in Newtonian mechanics. The prin ...

American Physical Society2022

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Rachid Guerraoui, Sadegh Farhadkhani, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

We study Byzantine collaborative learning, where n nodes seek to collectively learn from each others' local data. The data distribution may vary from one node to another. No node is trusted, and f < n nodes can behave arbitrarily. We prove that collaborati ...

2021

On compact representations of Voronoi cells of lattices

Matthias Schymura, Christoph Hunkenschröder

In a seminal work, Micciancio and Voulgaris (SIAM J Comput 42(3):1364-1391, 2013) described a deterministic single-exponential time algorithm for the closest vector problem (CVP) on lattices. It is based on the computation of the Voronoi cell of the given ...

SPRINGER HEIDELBERG2020

Wavelet analysis of the Besov regularity of Levy white noise

Julien René Pierre Fageot, Shayan Aziznejad

We characterize the local smoothness and the asymptotic growth rate of the Levy white noise. We do so by characterizing the weighted Besov spaces in which it is located. We extend known results in two ways. First, we obtain new bounds for the local smoothn ...

2020

One simulation to have them all: performance of the Bias Assignment Method against N-body simulations

Cheng Zhao

In this paper, we demonstrate that the information encoded in one single (sufficiently large) N-body simulation can be used to reproduce arbitrary numbers of halo catalogues, using approximated realizations of dark matter density fields with different init ...

OXFORD UNIV PRESS2020

Rational Krylov for Stieltjes matrix functions: convergence and pole selection

Stefano Massei

Evaluating the action of a matrix function on a vector, that is

x=f(\mathcal M)v

, is an ubiquitous task in applications. When

\mathcal M

is large, one usually relies on Krylov projection methods. In this paper, we provide effective choices for the pole ...

2019

Procrustes Metrics and Optimal Transport for Covariance Operators

Valentina Masarotto

Covariance operators play a fundamental role in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen-Loève expansion. These operators may themselves be subject to variation, for instance in con ...

EPFL2019

On compact representations of Voronoi cells of lattices

Matthias Schymura, Christoph Hunkenschröder

In a seminal work, Micciancio & Voulgaris (2010) described a deterministic single-exponential time algorithm for the Closest Vector Problem (CVP) on lattices. It is based on the computation of the Voronoi cell of the given lattice and thus may need exponen ...

SPRINGER INTERNATIONAL PUBLISHING AG2018

Low-latency speaker spotting with online diarization and detection

Sébastien Marcel, Nicholas Evans

This paper introduces a new task termed low-latency speaker spotting (LLSS). Related to security and intelligence applications, the task involves the detection, as soon as possible, of known speakers within multi-speaker audio streams. The paper describes ...

2018

Structure preserving model reduction of parametric Hamiltonian systems

Jan Sickmann Hesthaven, Babak Maboudi Afkham

While reduced-order models (ROMs) are popular for approximately solving large systems of differential equations, the stability of reduced models over long-time integration remains an open question. We present a greedy approach for ROM generation of paramet ...

2017

Cross-Intersecting Families of Vectors

János Pach, Gábor Tardos

Given a sequence of positive integers , let denote the family of all sequences of positive integers such that for all . Two families of sequences (or vectors), , are said to be -cross-intersecting if no matter how we select and , there are at least distinc ...

Springer Japan Kk2015

Modified group delay feature based total variability space modelling for speaker recognition

In this paper, modified group delay (MODGD) features are used to model target speakers in the Total Variability Space (TVS) framework for speaker recognition. MODGD based features have been shown to improve speaker recognition performance owing to the abil ...

2015

Low-rank tensor completion by Riemannian optimization

Daniel Kressner, Michael Maximilian Steinlechner

In tensor completion, the goal is to fill in missing entries of a partially known tensor under a low-rank constraint. We propose a new algorithm that performs Riemannian optimization techniques on the manifold of tensors of fixed multilinear rank. More spe ...

Springer2014

Method to determine the distribution of temperature sensors

Martin Vetterli, David Atienza Alonso, Juri Ranieri, Amina Chebira, Alessandro Vincenzi

Apparatus comprising M sensors for measuring the temperature on M locations of the apparatus and an estimator configured to estimate a temperature vector of the apparatus with N temperature variables, whereby the estimator is configured to approximate the ...

2014

Nonbinary Associative Memory With Exponential Pattern Retrieval Capacity and Iterative Learning

Mohammad Amin Shokrollahi, Amir Hesam Salavati, Krishna Kumar

We consider the problem of neural association for a network of nonbinary neurons. Here, the task is to first memorize a set of patterns using a network of neurons whose states assume values from a finite number of integer levels. Later, the same network sh ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Understanding and improving relational matrix factorization in recommender systems

Boi Faltings, Li Pu

Matrix factorization techniques such as the singular value decomposition (SVD) have had great success in recommender systems. We present a new perspective of SVD for constructing a latent space from the training data, which is justified by the theory of hy ...

ACM Press2013

A modulated gradient model for scalar transport in large-eddy simulation of the atmospheric boundary layer

Fernando Porté Agel, Hao Lu

As a simple alternative to the standard eddy-diffusivity closure, a nonlinear subgrid-scale (SGS) flux model is introduced and implemented in simulations of a neutral atmospheric boundary layer and a stable atmospheric boundary layer. The new model compute ...

American Institute of Physics2013

Incommensurate crystallography without additional dimensions

Philippe Kocian

It is shown that the Euclidean group of translations, when treated as a Lie group, generates translations not only in Euclidean space but on any space, curved or not. Translations are then not necessarily vectors (straight lines); they can be any curve com ...

International Union of Crystallography2013

Multiple signal classification technique for phase estimation from a fringe pattern

Pramod Rastogi, Rajshekhar Gannavarpu

The paper introduces a multiple signal classification technique based method for fringe analysis. In the proposed method, the phase of a fringe pattern is locally approximated as a polynomial. The polynomial phase signal is then transformed to obtain signa ...

Optical Society of America2012