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

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

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 ...

Path-following control is a critical technology for autonomous vehicles. However, time-varying parameters, parametric uncertainties, external disturbances, and complicated environments significantly challenge autonomous driving. We propose an iterative rob ...

We introduce robust principal component analysis from a data matrix in which the entries of its columns have been corrupted by permutations, termed Unlabeled Principal Component Analysis (UPCA). Using algebraic geometry, we establish that UPCA is a well-de ...

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

Air traffic noise emissions are responsible for a significant part of the overall environmental noise, especially in the vicinity of airports. Exposure to environmental noise is known to negatively impact health and to be associated with cardiovascular dis ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

BACKGROUND: Stereotactic radiosurgery (SRS) is one of the main treatment options in the management of small to medium size vestibular schwannomas (VSs), because of high tumor control rate and low cranial nerves morbidity. Series reporting long-term hearing ...

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 ...

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method woul ...

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...

In the distributed remote (CEO) source coding problem, many separate encoders observe independently noisy copies of an underlying source. The rate loss is the difference between the rate required in this distributed setting and the rate that would be requi ...

We propose a fast and scalable Polyatomic Frank-Wolfe (P-FW) algorithm for the resolution of high-dimensional LASSO regression problems. The latter improves upon traditional Frank-Wolfe methods by considering generalized greedy steps with polyatomic (i.e. ...

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

Chattez avec Graph Search

Random matrix methods for high-dimensional machine learning models

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

Unlabeled Principal Component Analysis and Matrix Completion

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Robust tunable acoustic impedance control on electroacoustic resonators for aircraft noise reduction

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Learned Compressive Representations for Single-Photon 3D Imaging

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Long-Term Hearing Outcome After Radiosurgery for Vestibular Schwannoma: A Systematic Review and Meta-Analysis

Optimal denoising of rotationally invariant rectangular matrices

Deep learning-based galaxy image deconvolution

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

The Price of Distributed: Rate Loss in the CEO Problem

A Fast and Scalable Polyatomic Frank-Wolfe Algorithm for the LASSO