Publications associées à Complex Wavelet Bases, Steerability, and the Marr-Like Pyramid

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

This paper studies kernel ridge regression in high dimensions under covariate shifts and analyzes the role of importance re-weighting. We first derive the asymptotic expansion of high dimensional kernels under covariate shifts. By a bias-variance decomposi ...

2024

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Michaël Unser, Rahul Parhi

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

IEEE Institute of Electrical and Electronics Engineers2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink, Tianfu Li

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

Amin Kaboli

Fault diagnosis plays an essential role in reducing the maintenance costs of rotating machinery manufacturing systems. In many real applications of fault detection and diagnosis, data tend to be imbalanced, meaning that the number of samples for some fault ...

MDPI2022

Graph Neural Networks With Lifting-Based Adaptive Graph Wavelets

Pascal Frossard, Chenglin Li, Mingxing Xu

Spectral-based graph neural networks (SGNNs) have been attracting increasing attention in graph representation learning. However, existing SGNNs are limited in implementing graph filters with rigid transforms and cannot adapt to signals residing on graphs ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Optical fibre based quench detection in HTS applications using machine learning classifiers

Bertrand Dutoit, Bertrand Dutoit, Arooj Akbar, Nicolo' Riva

A Mach-Zehnder Interferometer (MZI) based optical fibre sensing technique, developed and patented by EPFL, is an efficient and economical way to detect hotspots in High Temperature Superconductor (HTS) applications. Due to the MZI sensitivity being a compo ...

Elsevier2022

Single-Trace Clustering Power Analysis of the Point-Swapping Procedure in the Three Point Ladder of Cortex-M4 SIKE

Aymeric Genet, Novak Kaluderovic

In this paper, the recommended implementation of the post-quantum key exchange SIKE for Cortex-M4 is attacked through power analysis with a single trace by clustering with the k-means algorithm the power samples of all the invocations of the elliptic curve ...

Springer, Cham2022

Sketches, metrics and fast algorithms

Navid Nouri

As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

EPFL2022

Next generation modeling techniques for strong gravitational lensing and measuring the Hubble constant

Aymeric Alexandre Galan

For many years, observations of the Universe suggest a series problems with our theoretical models, particularly its dark energy and dark matter components. Fortunately, the Universe also provides us with a tool to solve these problems, called strong gravi ...

EPFL2022

JPEG XS-A New Standard for Visually Lossless Low-Latency Lightweight Image Coding

Touradj Ebrahimi

Joint Photographic Experts Group (JPEG) XS is a new International Standard from the JPEG Committee (formally known as ISO/International Electrotechnical Commission (IEC) JTC1/SC29/WG1). It defines an interoperable, visually lossless low-latency lightweight ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Touradj Ebrahimi, Pinar Akyazi

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

SPIE-INT SOC OPTICAL ENGINEERING2021

An Effective EMTR-Based High-Impedance Fault Location Method for Transmission Lines

Farhad Rachidi-Haeri, Rong Zeng

This article summarizes the electromagnetic time-reversal (EMTR) technique for fault location, and further numerically validates its effectiveness when the fault impedance is negligible. In addition, a specific EMTR model considering the fault impedance is ...

2021

SLITRONOMY: Towards a fully wavelet-based strong lensing inversion technique

Frédéric Courbin, Aymeric Alexandre Galan, Rémy Elie Joseph, Austin Chandler Peel

Strong gravitational lensing provides a wealth of astrophysical information on the baryonic and dark matter content of galaxies. It also serves as a valuable cosmological probe by allowing us to measure the Hubble constant independently of other methods. T ...

EDP SCIENCES S A2021

Deterministic error bounds for kernel-based learning techniques under bounded noise

Colin Neil Jones, Emilio Maddalena, Paul Scharnhorst

We consider the problem of reconstructing a function from a finite set of noise-corrupted samples. Two kernel algorithms are analyzed, namely kernel ridge regression and epsilon-support vector regression. By assuming the ground-truth function belongs to th ...

2021

Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

Silvestro Micera, Ivo Strauss, Simone Romeni

Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nerv ...

IOP PUBLISHING LTD2021

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

On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis

Luc Thévenaz, Simon Adrien Zaslawski, Zhisheng Yang

The benefits and limitations inherent to the 2D post-processing of measurements from Brillouin optical time-domain analyzers are investigated from a fundamental point of view. In a preliminary step, the impact of curve fitting on the precision of the estim ...

IEEE Institute of Electrical and Electronics Engineers2020

Systematic analysis of wavelet denoising methods for neural signal processing

Silvestro Micera

Objective. Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends o ...

IOP PUBLISHING LTD2020

Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations

Fabio Nobile, Simone Brugiapaglia

We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...

2021

The n-term Approximation of Periodic Generalized Levy Processes

Michaël Unser, John Paul Ward, Julien René Pierre Fageot

In this paper, we study the compressibility of random processes and fields, called generalized Levy processes, that are solutions of stochastic differential equations driven by d-dimensional periodic Levy white noises. Our results are based on the estimati ...

2020