Régis Lengellé

28 papers B 2C 2Misc 3Journal 11Unranked 10
YearRankTypeTitle / Venue / Authors
2023 J jnl
Sparse Decomposition of Heart Rate Using a Bernoulli-Gaussian Model: Application to Sleep Apnoea Detection.
Sensors
Bruno Muller, Régis Lengellé
2021 J jnl
Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rate.
Comput. Methods Programs Biomed.
Bruno Muller, Régis Lengellé
2017 — conf
Domain Adaptation Transfer Learning by Kernel Representation Adaptation.
ICPRAM (Revised Selected Papers)
Xiaoyi Chen, Régis Lengellé
2017 C conf
Domain Adaptation Transfer Learning by SVM Subject to a Maximum-Mean-Discrepancy-like Constraint.
ICPRAM
Xiaoyi Chen, Régis Lengellé
2014 C conf
Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of Clusters.
ICPRAM
Na Li, Nicolas Lefebvre, Régis Lengellé
2013 — conf
Learning General Gaussian Kernel Hyperparameters for SVR.
GSI
Fahed Abdallah, Hichem Snoussi, Hicham Laanaya, Régis Lengellé
2013 J jnl
Online Kernel Adaptive Algorithms With Dictionary Adaptation for MIMO Models.
IEEE Signal Process. Lett.
Chafic Saidé, Régis Lengellé, Paul Honeine, Roger Achkar
2013 — conf
Performance Analysis of Kernel Adaptive Filters based on LMS Algorithm.
Complex Adaptive Systems
Ibtissam Constantin, Régis Lengellé
2012 — conf
Dictionary adaptation for online prediction of time series data with kernels.
SSP
Chafic Saidé, Régis Lengellé, Paul Honeine, Cédric Richard, Roger Achkar
2011 B conf
Abnormal events detection using unsupervised One-Class SVM - Application to audio surveillance and evaluation -.
AVSS
Sébastien Lecomte, Régis Lengellé, Cédric Richard, François Capman, Bertrand Ravera
2011 J jnl
Maximum Margin One Class Support Vector Machines for multiclass problems.
Pattern Recognit. Lett.
Mireille Tohmé, Régis Lengellé
2009 — conf
Sequential Maximum Gradient Optimization for Support Vector detection.
EUSIPCO
Mireille Tohmé, Régis Lengellé
2008 Misc conf
F-SVR: A new learning algorithm for support vector regression.
ICASSP
Mireille Tohmé, Régis Lengellé
2006 J jnl
Nonlinear Regularized Wiener Filtering With Kernels: Application in Denoising MEG Data Corrupted by ECG.
IEEE Trans. Signal Process.
Ibtissam Constantin, Cédric Richard, Régis Lengellé, Laurent Soufflet
2005 — conf
Regularized kernel-based Wiener filtering. Application to magnetoencephalographic signals denoising.
ICASSP (4)
Ibtissam Constantin, Cédric Richard, Régis Lengellé, Laurent Soufflet
2004 — conf
A sequential approach for multi-class discriminant analysis with kernels.
ICASSP (5)
Fahed Abdallah, Cédric Richard, Régis Lengellé
2004 J jnl
An improved training algorithm for nonlinear kernel discriminants.
IEEE Trans. Signal Process.
Fahed Abdallah, Cédric Richard, Régis Lengellé
2003 — conf
Kernel second-order discriminants versus support vector machines.
ICASSP (6)
Fahed Abdallah, Cédric Richard, Régis Lengellé
2002 — conf
Adaptive diffusion and discriminant analysis for complexity control of time-frequency detectors.
EUSIPCO
Julien Gosme, Paulo Gonçalves, Cédric Richard, Régis Lengellé
2002 J jnl
Bayes-optimal detectors design using relevant second-order criteria.
IEEE Signal Process. Lett.
Cédric Richard, Régis Lengellé, Fahed Abdallah
2002 — conf
On equivalence between detectors obtained from second-order measures of performance.
EUSIPCO
Fahed Abdallah, Cédric Richard, Régis Lengellé
2000 Misc conf
On the linear relations connecting the components of the discrete Wigner distribution in the case of real-valued signals.
ICASSP
Cédric Richard, Régis Lengellé
1999 J jnl
Data-driven design and complexity control of time-frequency detectors.
Signal Process.
Cédric Richard, Régis Lengellé
1998 Misc conf
Structural risk minimization for reduced-bias time-frequency-based detectors design.
ICASSP
Cédric Richard, Régis Lengellé
1997 J jnl
Joint recursive implementation of time - frequency representations and their modified version by the reassignment method.
Signal Process.
Cédric Richard, Régis Lengellé
1996 J jnl
Training MLPs layer by layer using an objective function for internal representations.
Neural Networks
Régis Lengellé, Thierry Denoeux
1995 B conf
Performance analysis of a MLP weight initialization algorithm.
ESANN
Mohamed Karouia, Régis Lengellé, Thierry Denoeux
1993 J jnl
Initializing back propagation networks with prototypes.
Neural Networks
Thierry Denoeux, Régis Lengellé