Régis Lengellé - researchr alias

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Viewing Publication 1 - 27 from 27

2023

Sparse Decomposition of Heart Rate Using a Bernoulli-Gaussian Model: Application to Sleep Apnoea DetectionBruno Muller, Régis Lengellé. sensors, 23(7):3743, April 2023. [doi]

2021

Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rateBruno Muller, Régis Lengellé. cmpb, 208:106280, 2021. [doi]

2017

Domain Adaptation Transfer Learning by SVM Subject to a Maximum-Mean-Discrepancy-like ConstraintXiaoyi Chen, Régis Lengellé. icpram 2017: 89-95 [doi]

Domain Adaptation Transfer Learning by Kernel Representation AdaptationXiaoyi Chen, Régis Lengellé. icpram 2018: 45-61 [doi]

2014

Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of ClustersNa Li, Nicolas Lefebvre, Régis Lengellé. icpram 2014: 255-262 [doi]

2013

Learning General Gaussian Kernel Hyperparameters for SVRFahed Abdallah, Hichem Snoussi, Hicham Laanaya, Régis Lengellé. gsi 2013: 677-684 [doi]

Performance Analysis of Kernel Adaptive Filters based on LMS AlgorithmIbtissam Constantin, Régis Lengellé. complexsystems 2013: 39-45 [doi]

Online Kernel Adaptive Algorithms With Dictionary Adaptation for MIMO ModelsChafic Saide, Régis Lengellé, Paul Honeine, Roger Achkar. spl, 20(5):535-538, 2013. [doi]

2012

Dictionary adaptation for online prediction of time series data with kernelsChafic Saide, Régis Lengellé, Paul Honeine, Cédric Richard, Roger Achkar. gacm 2012: 604-607 [doi]

2011

Abnormal events detection using unsupervised One-Class SVM - Application to audio surveillance and evaluation -Sébastien Lecomte, Régis Lengellé, Cédric Richard, François Capman, Bertrand Ravera. avss 2011: 124-129 [doi]

Maximum Margin One Class Support Vector Machines for multiclass problemsMireille Tohmé, Régis Lengellé. prl, 32(13):1652-1658, 2011. [doi]

2009

Sequential Maximum Gradient Optimization for Support Vector detectionMireille Tohmé, Régis Lengellé. eusipco 2009: 1705-1709 [doi]

2006

Nonlinear Regularized Wiener Filtering With Kernels: Application in Denoising MEG Data Corrupted by ECGIbtissam Constantin, Cédric Richard, Régis Lengellé, Laurent Soufflet. tsp, 54(12):4796-4806, 2006. [doi]

2005

Regularized kernel-based Wiener filtering. Application to magnetoencephalographic signals denoisingIbtissam Constantin, Cédric Richard, Régis Lengellé, Laurent Soufflet. icassp 2005: 289-292 [doi]

2004

A sequential approach for multi-class discriminant analysis with kernelsFahed Abdallah, Cédric Richard, Régis Lengellé. icassp 2004: 453-456 [doi]

An improved training algorithm for nonlinear kernel discriminantsFahed Abdallah, Cédric Richard, Régis Lengellé. tsp, 52(10):2798-2806, 2004. [doi]

2003

Kernel second-order discriminants versus support vector machinesFahed Abdallah, Cédric Richard, Régis Lengellé. icassp 2003: 149-152 [doi]

2002

On equivalence between detectors obtained from second-order measures of performanceFahed Abdallah, Cédric Richard, Régis Lengellé. eusipco 2002: 1-4 [doi]

Adaptive diffusion and discriminant analysis for complexity control of time-frequency detectorsJulien Gosme, Paulo Gonçalves, Cédric Richard, Régis Lengellé. eusipco 2002: 1-4 [doi]

Bayes-optimal detectors design using relevant second-order criteriaCédric Richard, Régis Lengellé, Fahed Abdallah. spl, 9(1):32-33, 2002. [doi]

2000

On the linear relations connecting the components of the discrete Wigner distribution in the case of real-valued signalsCédric Richard, Régis Lengellé. icassp 2000: 85-88 [doi]

1999

Data-driven design and complexity control of time-frequency detectorsCédric Richard, Régis Lengellé. sigpro, 77(1):37-48, 1999. [doi]

1998

Structural risk minimization for reduced-bias time-frequency-based detectors designCédric Richard, Régis Lengellé. icassp 1998: 2397-2400 [doi]

1997

Joint recursive implementation of time - frequency representations and their modified version by the reassignment methodCédric Richard, Régis Lengellé. sigpro, 60(2):163-179, 1997. [doi]

1996

Training MLPs layer by layer using an objective function for internal representationsRégis Lengellé, Thierry Denoeux. NN, 9(1):83-97, 1996. [doi]

1995

Performance analysis of a MLP weight initialization algorithmMohamed Karouia, Régis Lengellé, Thierry Denoeux. esann 1995: [doi]

1993

Initializing back propagation networks with prototypesThierry Denoeux, Régis Lengellé. NN, 6(3):351-363, 1993. [doi]

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