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

Faster Algorithms for Integer Programs with Block Structure

Friedrich Eisenbrand, Kim-Manuel Klein, Christoph Hunkenschröder

We consider integer programming problems max {c^Tx : A x = b, l

Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik2018

Fast hierarchical solvers for symmetric eigenvalue problems

In this thesis we address the computation of a spectral decomposition for symmetric banded matrices. In light of dealing with large-scale matrices, where classical dense linear algebra routines are not applicable, it is essential to design alternative tech ...

EPFL2018

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

Stefano Massei

A Quasi Toeplitz (QT) matrix is a semi-infinite matrix of the kind

A = T(a) + E

where

T(a) = (aj-i)_{i,j\in \mathbb{Z}_{+}}

,

E = (e_{i,j})_{i,j\in\mathbb{Z}_{+}}

is compact and the norms

\| a\|_{\mathcal{W}} =\sum_{i\in\mathbb{Z}} |a|_j

and $|E|_{ ...

MATHICSE2018

Structure from sound with incomplete data

Martin Vetterli, Ivan Dokmanic, Gilles Baechler, Miranda Krekovic

In this paper, we consider the problem of jointly localizing a microphone array and identifying the direction of arrival of acoustic events. Under the assumption that the sources are in the far field, this problem can be formulated as a constrained low-ran ...

2018

How little does non-exact recovery help in group testing?

Volkan Cevher, Jonathan Mark Scarlett

We consider the group testing problem, in which one seeks to identify a subset of defective items within a larger set of items based on a number of tests. We characterize the information-theoretic performance limits in the presence of list decoding, in whi ...

Ieee2017

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices

Volkan Cevher, Jonathan Mark Scarlett

Linear sketching is a powerful tool for the problem of sparse signal recovery, having numerous applications such as compressive sensing, data stream computing, graph sketching, and routing. Motivated by applications where the \emph{positions} of the non-ze ...

2016

Learning-Based Compressive Subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The problem of recovering a structured signal

\mathbf{x} \in \mathbb{C}^p

from a set of dimensionality-reduced linear measurements

\mathbf{b} = \mathbf {A}\mathbf {x}

arises in a variety of applications, such as medical imaging, spectroscopy, Fourier o ...

Ieee-Inst Electrical Electronics Engineers Inc2016

A block algorithm for computing antitriangular factorizations of symmetric matrices

Daniel Kressner, Zvonimir Bujanovic

Any symmetric matrix can be reduced to antitriangular form in finitely many steps by orthogonal similarity transformations. This form reveals the inertia of the matrix and has found applications in, e.g., model predictive control and constraint preconditio ...

Springer2016

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Volkan Cevher

The estimation of a random vector with independent components passed through a linear transform followed by a componentwise (possibly nonlinear) output map arises in a range of applications. Approximate message passing (AMP) methods, based on Gaussian appr ...

2016

Compressed Sensing of Memoryless Sources

Saeid Haghighatshoar

Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...

EPFL2014

Converse Bounds for Noisy Group Testing with Arbitrary Measurement Matrices

Graph Chatbot

Chat with Graph Search

Faster Algorithms for Integer Programs with Block Structure

Fast hierarchical solvers for symmetric eigenvalue problems

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

Structure from sound with incomplete data

How little does non-exact recovery help in group testing?

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices

Learning-Based Compressive Subsampling

A block algorithm for computing antitriangular factorizations of symmetric matrices

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Compressed Sensing of Memoryless Sources

Faster Algorithms for Integer Programs with Block Structure

MATHICSE Technical Report : Quasi-Toeplitz matrix arithmetic : a Matlab toolbox

Fast hierarchical solvers for symmetric eigenvalue problems

Learning-Based Compressive Subsampling

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

How little does non-exact recovery help in group testing?

Compressed Sensing of Memoryless Sources

A block algorithm for computing antitriangular factorizations of symmetric matrices

Structure from sound with incomplete data

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices