Publications related to Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

Nicolas Macris, Florent Gérard Krzakala, Jean François Emmanuel Barbier

There has been definite progress recently in proving the variational single-letter formula given by the heuristic replica method for various estimation problems. In particular, the replica formula for the mutual information in the case of noisy linear esti ...

IEEE2018

New Approach to Identifying Critical Initial Conditions for Extreme Flood Simulations in a Semicontinuous Simulation Framework

Anton Schleiss, Javier García Hernández, Bettina Schaefli, Fränz Zeimetz, Guillaume Mathieu Artigue

Extreme flood simulation with synthetic extreme precipitation events raises unavoidable questions about the choice of initial conditions. State-of-the-art extreme flood estimation frameworks propose to address these questions with the help of semicontinuou ...

2018

A Row-Column Accessed Dynamic Element Matching DAC Architecture for SAR ADCs

Mustafa Kilic, Selman Ergünay, Yusuf Leblebici

Capacitor mismatch in high resolution Successive Approximation Register (SAR) Analog to Digital Converters (ADCs) causes non-linearity effects that reduce the Spurious-Free Dynamic Range (SFDR). This paper presents a novel dynamic element matching (DEM) te ...

IEEE2018

Polarization of the Renyi Information Dimension With Applications to Compressed Sensing

Emmanuel Abbé, Saeid Haghighatshoar

In this paper, we show that the Hadamard matrix acts as an extractor over the reals of the Renyi Information Dimension (RID), in an analogous way to how it acts as an extractor of the discrete entropy over finite fields. More precisely, we prove that the R ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Dimensionality Reduction in Dynamic Optimization under Uncertainty

Napat Rujeerapaiboon

Dynamic optimization problems affected by uncertainty are ubiquitous in many application domains. Decision makers typically model the uncertainty through random variables governed by a probability distribution. If the distribution is precisely known, then ...

EPFL2016

Fast recovery and approximation of hidden Cauchy structure

Robert Gerhard Jérôme Luce

We derive an algorithm of optimal complexity which determines whether a given matrix is a Cauchy matrix, and which exactly recovers the Cauchy points defining a Cauchy matrix from the matrix entries. Moreover, we study how to approximate a given matrix by ...

Elsevier Science Inc2016

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the first

k

eigenvectors of the similarity matrix' Laplacian, whose computati ...

Ieee2016

Optimal acoustic rake receiver

Martin Vetterli, Ivan Dokmanic, Robin Scheibler

An acoustic processing method for M acoustic receivers comprising the steps of: Determining a beamforming weight vector with M weights for the M acoustic receivers based on at least one the steering vector of at least one real acoustic source, on steering ...

2016

Compressive PCA for Low-Rank Matrices on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid

We introduce a novel framework for an approxi- mate recovery of data matrices which are low-rank on graphs, from sampled measurements. The rows and columns of such matrices belong to the span of the first few eigenvectors of the graphs constructed between ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite-dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

2015

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

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The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

New Approach to Identifying Critical Initial Conditions for Extreme Flood Simulations in a Semicontinuous Simulation Framework

A Row-Column Accessed Dynamic Element Matching DAC Architecture for SAR ADCs

Polarization of the Renyi Information Dimension With Applications to Compressed Sensing

Dimensionality Reduction in Dynamic Optimization under Uncertainty

Fast recovery and approximation of hidden Cauchy structure

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Optimal acoustic rake receiver

Compressive PCA for Low-Rank Matrices on Graphs

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Polarization of the Renyi Information Dimension With Applications to Compressed Sensing

Dimensionality Reduction in Dynamic Optimization under Uncertainty

Optimal acoustic rake receiver

Fast recovery and approximation of hidden Cauchy structure

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

New Approach to Identifying Critical Initial Conditions for Extreme Flood Simulations in a Semicontinuous Simulation Framework

A Row-Column Accessed Dynamic Element Matching DAC Architecture for SAR ADCs

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Compressive PCA for Low-Rank Matrices on Graphs

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points