A Quadratic Loss Multi-Class SVM - Emmanuel Monfrini; Yann Guermeur (CoRR, 2008)

Optimal SIR algorithm vs. fully adapted auxiliary particle filter: A matter of conditional independence. - François Desbouvries; Yohan Petetin; Emmanuel Monfrini (ICASSP, 2011)

Unsupervised segmentation of switching pairwise Markov chains. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Wojciech Pieczynski (ISPA, 2011)

A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies. - Yann Guermeur; Emmanuel Monfrini (Informatica, 2011)

Unsupervised segmentation of nonstationary pairwise Markov Chains using evidential priors. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Wojciech Pieczynski (EUSIPCO, 2012)

Dempster-Shafer fusion of multisensor signals in nonstationary Markovian context. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Wojciech Pieczynski; Amar Aïssani (EURASIP J. Adv. Signal Process., 2012)

Unsupervised Segmentation of Random Discrete Data Hidden With Switching Noise Distributions. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Wojciech Pieczynski (IEEE Signal Process. Lett., 2012)

Implementation of Unsupervised Statistical Methods for Low-Quality Iris Segmentation. - Meriem Yahiaoui; Emmanuel Monfrini; Bernadette Dorizzi (SITIS, 2014)

Phasic Triplet Markov Chains. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Wojciech Pieczynski; Amar Aissani (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Exact fast smoothing in switching models with application to stochastic volatility. - Ivan Gorynin; Stéphane Derrode; Emmanuel Monfrini; Wojciech Pieczynski (EUSIPCO, 2015)

2-Step robust vertebra segmentation. - Jean-Baptiste Courbot; Edmond Rust; Emmanuel Monfrini; Christophe Collet 001 (IPTA, 2015)

Detection of faint extended sources in hyperspectral data and application to HDF-S MUSE observations. - Jean-Baptiste Courbot; Vincent Mazet; Emmanuel Monfrini; Christophe Collet 001 (ICASSP, 2016)

Unsupervised learning of Markov-switching stochastic volatility with an application to market data. - Ivan Gorynin; Emmanuel Monfrini; Wojciech Pieczynski (MLSP, 2016)

Fast filtering with new sparse transition Markov chains. - Ivan Gorynin; Emmanuel Monfrini; Wojciech Pieczynski (SSP, 2016)

Oriented Triplet Markov fields for hyperspectral image segmentation. - Jean-Baptiste Courbot; Emmanuel Monfrini; Vincent Mazet; Christophe Collet 001 (WHISPERS, 2016)

Markov Chains for unsupervised segmentation of degraded NIR iris images for person recognition. - Meriem Yahiaoui; Emmanuel Monfrini; Bernadette Dorizzi (Pattern Recognit. Lett., 2016)

Pairwise Markov models for stock index forecasting. - Ivan Gorynin; Emmanuel Monfrini; Wojciech Pieczynski (EUSIPCO, 2017)

Unsupervised learning of asymmetric high-order autoregressive stochastic volatility model. - Ivan Gorynin; Emmanuel Monfrini; Wojciech Pieczynski (ICASSP, 2017)

Unsupervised Segmentation of Nonstationary Data using Triplet Markov Chains. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Kadda Beghdad Bey; Ahmed Habbouchi; Wojciech Pieczynski (ICEIS (1), 2017)

Triplet Markov Chains Based- Estimation of Nonstationary Latent Variables Hidden with Independent Noise. - Mohamed El Yazid Boudaren; Emmanuel Monfrini; Kadda Beghdad Bey; Ahmed Habbouchi; Wojciech Pieczynski (ICEIS (Revised Selected Papers), 2017)

Fast smoothing in switching approximations of non-linear and non-Gaussian models. - Ivan Gorynin; Stéphane Derrode; Emmanuel Monfrini; Wojciech Pieczynski (Comput. Stat. Data Anal., 2017)

Extended faint source detection in astronomical hyperspectral images. - Jean-Baptiste Courbot; Vincent Mazet; Emmanuel Monfrini; Christophe Collet 001 (Signal Process., 2017)

Fast Filtering in Switching Approximations of Nonlinear Markov Systems With Applications to Stochastic Volatility. - Ivan Gorynin; Stéphane Derrode; Emmanuel Monfrini; Wojciech Pieczynski (IEEE Trans. Autom. Control., 2017)

Triplet Markov Trees for Image Segmentation. - Jean-Baptiste Courbot; Emmanuel Monfrini; Vincent Mazet; Christophe Collet 001 (SSP, 2018)

Oriented Triplet Markov Fields. - Jean-Baptiste Courbot; Emmanuel Monfrini; Vincent Mazet; Christophe Collet 001 (Pattern Recognit. Lett., 2018)

Assessing the segmentation performance of pairwise and triplet Markov models. - Ivan Gorynin; Hugo Gangloff; Emmanuel Monfrini; Wojciech Pieczynski (Signal Process., 2018)

Pairwise Markov fields for segmentation in astronomical hyperspectral images. - Jean-Baptiste Courbot; Vincent Mazet; Emmanuel Monfrini; Christophe Collet 001 (Signal Process., 2019)

Unsupervised segmentation of stents corrupted by artifacts in medical X-ray images. - Hugo Gangloff; Emmanuel Monfrini; Christophe Collet 001; Nabil Chakfé (IPTA, 2020)

Improved centerline tracking for new descriptors of atherosclerotic aortas. - Hugo Gangloff; Emmanuel Monfrini; Mohamed Zied Ghariani; Mickaël Ohana; Christophe Collet 001; Nabil Chakfé (IPTA, 2020)

Hidden Markov Chains, Entropic Forward-Backward, and Part-Of-Speech Tagging. - Elie Azeraf; Emmanuel Monfrini; Emmanuel Vignon; Wojciech Pieczynski (CoRR, 2020)

Using the Naive Bayes as a discriminative classifier. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (CoRR, 2020)

Highly Fast Text Segmentation With Pairwise Markov Chains. - Elie Azeraf; Emmanuel Monfrini; Emmanuel Vignon; Wojciech Pieczynski (CIST, 2021)

Fast Image Segmentation with Contextual Scan and Markov Chains. - Clément Fernandes; Thomas Monti; Emmanuel Monfrini; Wojciech Pieczynski (EUSIPCO, 2021)

Introducing the Hidden Neural Markov Chain Framework. - Elie Azeraf; Emmanuel Monfrini; Emmanuel Vignon; Wojciech Pieczynski (ICAART (2), 2021)

Unsupervised Image Segmentation with Spatial Triplet Markov Trees. - Hugo Gangloff; Jean-Baptiste Courbot; Emmanuel Monfrini; Christophe Collet 001 (ICASSP, 2021)

Using the Naive Bayes as a discriminative model. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (ICMLC, 2021)

Unsupervised image segmentation with Gaussian Pairwise Markov Fields. - Hugo Gangloff; Jean-Baptiste Courbot; Emmanuel Monfrini; Christophe Collet 001 (Comput. Stat. Data Anal., 2021)

On Equivalence between Linear-chain Conditional Random Fields and Hidden Markov Chains. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (ICAART (3), 2022)

Improving Usual Naive Bayes Classifier Performances with Neural Naive Bayes based Models. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (ICPRAM, 2022)

Deriving discriminative classifiers from generative models. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (CoRR, 2022)

Linear chain conditional random fields, hidden Markov models, and related classifiers. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (CoRR, 2023)

Equivalence between LC-CRF and HMM, and Discriminative Computing of HMM-Based MPM and MAP. - Elie Azeraf; Emmanuel Monfrini; Wojciech Pieczynski (Algorithms, 2023)