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Herwig Wendt

16 accepted papers

2025

Estimating Instrument Spectral Response Functions Using Sparse Representations and Quadratic Envelopes

Jihanne El Haouari, Marcus Carlsson, Jean-Yves Tourneret, Herwig Wendt, Jean-Michel Gaucel, Christelle Pittet
ICASSP 2025accepted

The estimation of high resolution spectrometer Instrument Spectral Response Functions (ISRFs) is crucial because an imperfect knowledge of these functions can induce errors in the measurements. The state-of-the-art for this problem currently relies on the use of parametric models, which frequently l…

Cited by 0Source ↗Scholar ↗
2022

Counting the Number of Different Scaling Exponents in Multivariate Scale-Free Dynamics: Clustering by Bootstrap in the Wavelet Domain

Charles-Gérard Lucas, Patrice Abry, Herwig Wendt, Gustavo Didier
ICASSP 2022accepted

Multivariate selfsimilarity has become a classical tool to analyze collections of time series recorded jointly on one same system. Often, it amounts to estimating as many scaling exponents as time series. However, this leaves open the important question how many such scaling exponents are actually d…

Cited by 4Source ↗Scholar ↗
2021

Graph Constrained Data Representation Learning for Human Motion Segmentation

Mariella Dimiccoli, Lluís Garrido, Guillem Rodriguez-Corominas, Herwig Wendt
ICCV 2021poster

Recently, transfer subspace learning based approaches have shown to be a valid alternative to unsupervised subspace clustering and temporal data clustering for human motion segmentation (HMS). These approaches leverage prior knowledge from a source domain to improve clustering performance on a targe…

Cited by 8PDF ↗code ↗Scholar ↗
2021

Learning grounded word meaning representations on similarity graphs

Mariella Dimiccoli, Herwig Wendt, Pau Batlle Franch
EMNLP 2021main

This paper introduces a novel approach to learn visually grounded meaning representations of words as low-dimensional node embeddings on an underlying graph hierarchy. The lower level of the hierarchy models modality-specific word representations, conditioned to another modality, through dedicated b…

Cited by 1Source ↗PDF ↗code ↗Scholar ↗
2019

A Quasi-Newton Algorithm on the Orthogonal Manifold for NMF with Transform Learning

Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte
ICASSP 2019accepted

Nonnegative matrix factorization (NMF) is a popular method for audio spectral unmixing. While NMF is traditionally applied to off-the-shelf time-frequency representations based on the short-time Fourier or Cosine transforms, the ability to learn transforms from raw data attracts increasing attention…

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2019

Bootstrap-based Bias Reduction for the Estimation of the Self-similarity Exponents of Multivariate Time Series

Herwig Wendt, Patrice Abry, Gustavo Didier
ICASSP 2019accepted

Self-similarity has become a well-established modeling framework in several fields of application and its multivariate formulation is of ever-increasing importance in the Big Data era. Multivariate Hurst exponent estimation has thus received a great deal of attention recently, with wavelet eigenvalu…

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2019

Detection and Estimation of Delays in Bivariate Self-similarity: Bootstrapped Complex Wavelet Coherence

Gustavo Didier, Herwig Wendt, Patrice Abry
ICASSP 2019accepted

The self-similarity paradigm enables the analysis of scale-free temporal dynamics and has been widely used in a large set of real-world applications. However, in a multivariate setting, delays amongst components significantly impair the estimation of scale-free parameters. The first framework for th…

Cited by 1Source ↗Scholar ↗
2019

Majorization-minimization Algorithms for Convolutive NMF with the Beta-divergence

Dylan Fagot, Herwig Wendt, Cédric Févotte, Paris Smaragdis
ICASSP 2019accepted

Nonnegative matrix factorization (NMF) has become a method of choice for spectrogram decomposition. However, its inability to capture dependencies across columns of the input motivated the introduction of a variant, convolutive NMF. While algorithms for solving the convolutive NMF problem were previ…

Cited by 0Source ↗Scholar ↗
2018

Assessing Cross-Dependencies Using Bivariate Multifractal Analysis

Herwig Wendt, Roberto F. Leonarduzzi, Patrice Abry, Stéphane G. Roux, Stéphane Jaffard, Stéphane Seuret
ICASSP 2018accepted

Multifractal analysis, notably with its recent wavelet-leader based formulation, has nowadays become a reference tool to characterize scale-free temporal dynamics in time series. It proved successful in numerous applications very diverse in nature. However, such successes remained restricted to univ…

Cited by 0Source ↗Scholar ↗
2017

Bayesian-driven criterion to automatically select the regularization parameter in the ℓ1-Potts model

Jordan Frécon, Nelly Pustelnik, Nicolas Dobigeon, Herwig Wendt, Patrice Abry
ICASSP 2017accepted

This contribution focuses, within the ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -Potts model, on the automated estimation of the regularization parameter balancing the ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="ht…

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2017

Multivariate scale-free dynamics: Testing fractal connectivity

Sébastien Combrexelle, Herwig Wendt, Gustavo Didier, Patrice Abry
ICASSP 2017accepted

Scale-free dynamics commonly appear in individual components of multivariate data. Yet, while the behavior of cross-components is crucial in modeling real-world multivariate data, their examination often suggests departures from exact multivariate self-similarity (also termed fractal connectivity).…

Cited by 4Source ↗Scholar ↗
2017

P-leader multifractal analysis for text type identification

Roberto F. Leonarduzzi, Patrice Abry, Stéphane Jaffard, Herwig Wendt, L. Gournay, Tita Kyriacopoulou +2
ICASSP 2017accepted

Among many research efforts devoted to automated art investigations, the problem of quantification of literary style remains current. Meanwhile, linguists and computer scientists have tried to sort out texts according to their types or authors. We use the recently-introduced p-leader multifractal fo…

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2016

A Bayesian framework for the multifractal analysis of images using data augmentation and a whittle approximation

Sébastien Combrexelle, Herwig Wendt, Yoann Altmann, Jean-Yves Tourneret, Steve McLaughlin, Patrice Abry
ICASSP 2016accepted

Texture analysis is an image processing task that can be conducted using the mathematical framework of multifractal analysis to study the regularity fluctuations of image intensity and the practical tools for their assessment, such as (wavelet) leaders. A recently introduced statistical model for le…

Cited by 0Source ↗Scholar ↗
2015

A Bayesian approach for the joint estimation of the multifractality parameter and integral scale based on the Whittle approximation

Sébastien Combrexelle, Herwig Wendt, Patrice Abry, Nicolas Dobigeon, Stephen McLaughlin, Jean-Yves Tourneret
ICASSP 2015accepted

Multifractal analysis is a powerful tool used in signal processing. Multifractal models are essentially characterized by two parameters, the multifractality parameter c2 and the integral scale A (the time scale beyond which multifractal properties vanish). Yet, most applications concentrate on estim…

Cited by 3Source ↗Scholar ↗
2015

Random projection and multiscale wavelet leader based anomaly detection and address identification in internet traffic

Romain Fontugne, Patrice Abry, Kensuke Fukuda, Pierre Borgnat, Johan Mazel, Herwig Wendt +1
ICASSP 2015accepted

We present a new anomaly detector for data traffic, ‘SMS’, based on combining random projections (sketches) with multiscale analysis, which has low computational complexity. The sketches allow ‘normal’ traffic to be automatically and robustly extracted, and anomalies detected, without the need for t…

Cited by 0Source ↗Scholar ↗