21 citations · 21 across the 7 of their papers we have counts for
7 papers
Robust Expectation-Maximization for Covariance Estimation in SIRV Models with Missing Data: Application to InSAR Time Series
M. Cherifi, M. N. El Korso, A. Hippert-Ferrer +1
This paper presents a robust Expectation-Maximization framework for covariance estimation in Scale-Invariant Random Vector (SIRV) models with missing data under ignorable missingne…
Leveraging Low-rank Factorizations of Conditional Correlation Matrices in Graph Learning
Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard +1
This paper addresses the problem of learning an undirected graph from data gathered at each nodes. Within the graph signal processing framework, the topology of such graph can be l…
Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches
Alexandre Hippert-Ferrer, Aude Sportisse, Amirhossein Javaheri +2
This tutorial aims to provide signal processing (SP) and machine learning (ML) practitioners with vital tools, in an accessible way, to answer the question: How to deal with missin…
Learning Graphical Factor Models with Riemannian Optimization
Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian +2
Graphical models and factor analysis are well-established tools in multivariate statistics. While these models can be both linked to structures exhibited by covariance and precisio…
A Robust and Flexible EM Algorithm for Mixtures of Elliptical Distributions with Missing Data
Florian Mouret, Alexandre Hippert-Ferrer, Frédéric Pascal +1
This paper tackles the problem of missing data imputation for noisy and non-Gaussian data. A classical imputation method, the Expectation Maximization (EM) algorithm for Gaussian m…
Riemannian classification of EEG signals with missing values
Alexandre Hippert-Ferrer, Ammar Mian, Florent Bouchard +1
This paper proposes a strategy to handle missing data for the classification of electroencephalograms using covariance matrices. It relies on the observed-data likelihood within an…
Robust low-rank covariance matrix estimation with a general pattern of missing values
Alexandre Hippert-Ferrer, Mohammed Nabil El Korso, Arnaud Breloy +1
This paper tackles the problem of robust covariance matrix estimation when the data is incomplete. Classical statistical estimation methodologies are usually built upon the Gaussia…