Publications related to Converse Bounds for Noisy Group Testing with Arbitrary Measurement Matrices

Spectral Estimators for High-Dimensional Matrix Inference

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Daniel Kressner, Haoze He

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Philadelphia2024

Optimal denoising of rotationally invariant rectangular matrices

Florent Gérard Krzakala, Lenka Zdeborová, Emanuele Troiani, Vittorio Erba

In this manuscript we consider denoising of large rectangular matrices: given a noisy observation of a signal matrix, what is the best way of recovering the signal matrix itself? For Gaussian noise and rotationally-invariant signal priors, we completely ch ...

2022

The double exponential runtime is tight for 2-stage stochastic ILPs

Kim-Manuel Klein, Klaus Jansen, Alexandra Anna Lassota

We consider fundamental algorithmic number theoretic problems and their relation to a class of block structured Integer Linear Programs (ILPs) called 2-stage stochastic. A 2-stage stochastic ILP is an integer program of the form min{c(T)x vertical bar Ax = ...

SPRINGER HEIDELBERG2022

Robust Differentiable SVD

Pascal Fua, Mathieu Salzmann, Zheng Dang, Wei Wang, Yinlin Hu

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

2021

Nonlinear Finite Elements in Dynamics

This report focuses on the implementation of the finite element method for nonlinear dynamical problems arising in solid mechanics. The theory of continuum mechanics is extensively covered in the literature and it is assumed the reader is already familiar ...

2020

Efficient Distributed Transposition Of Large-Scale Multigraphs And High-Cardinality Sparse Matrices

Felix Schürmann, Bruno Ricardo Da Cunha Magalhães

Graph-based representations underlie a wide range of scientific problems. Graph connectivity is typically represented as a sparse matrix in the Compressed Sparse Row format. Large-scale graphs rely on distributed storage, allocating distinct subsets of row ...

2020

Global eigenvalue distribution of matrices defined by the skew-shift

Marius Christopher Lemm

We consider large Hermitian matrices whose entries are defined by evaluating the exponential function along orbits of the skew-shift

\binom{j}{2} \omega+jy+x \mod 1

for irrational

\omega

. We prove that the eigenvalue distribution of these matrices conv ...

2019

Fourier dimensionality reduction for fast radio transients

Jean-Philippe Thiran, Yves Wiaux, Vijay Kartik, Ming Jiang

In the context of next-generation radio interferometers, we are facing a big challenge of how to economically process data. The classical dimensionality reduction technique, averaging visibilities on time, may dilute fast radio transients (FRT). We propose ...

2019

Convergence of the Exponentiated Gradient Method with Armijo Line Search

Volkan Cevher, Yen-Huan Li

Consider the problem of minimizing a convex differentiable function on the probability simplex, spectrahedron, or set of quantum density matrices. We prove that the expo-nentiated gradient method with Armijo line search always converges to the optimum, if ...

2018

Converse Bounds for Noisy Group Testing with Arbitrary Measurement Matrices

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Spectral Estimators for High-Dimensional Matrix Inference

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Optimal denoising of rotationally invariant rectangular matrices

The double exponential runtime is tight for 2-stage stochastic ILPs

Robust Differentiable SVD

Nonlinear Finite Elements in Dynamics

Efficient Distributed Transposition Of Large-Scale Multigraphs And High-Cardinality Sparse Matrices

Global eigenvalue distribution of matrices defined by the skew-shift

Fourier dimensionality reduction for fast radio transients

Convergence of the Exponentiated Gradient Method with Armijo Line Search

Nonlinear Finite Elements in Dynamics

Optimal denoising of rotationally invariant rectangular matrices

Robust Differentiable SVD

Spectral Estimators for High-Dimensional Matrix Inference

Global eigenvalue distribution of matrices defined by the skew-shift

Efficient Distributed Transposition Of Large-Scale Multigraphs And High-Cardinality Sparse Matrices

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Fourier dimensionality reduction for fast radio transients

Convergence of the Exponentiated Gradient Method with Armijo Line Search

The double exponential runtime is tight for 2-stage stochastic ILPs