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12/30/2022
Mixture of von Mises-Fisher distribution with sparse prototypes
Mixtures of von Mises-Fisher distributions can be used to cluster data o...
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12/27/2022
Fast and fully-automated histograms for large-scale data sets
G-Enum histograms are a new fast and fully automated method for irregula...
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12/27/2022
Challenges in anomaly and change point detection
This paper presents an introduction to the state-of-the-art in anomaly a...
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12/22/2022
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
Machine learning (ML) models are nowadays used in complex applications i...
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12/22/2022
Federated Learning – Methods, Applications and beyond
In recent years the applications of machine learning models have increas...
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12/22/2022
Co-clustering based exploratory analysis of mixed-type data tables
Co-clustering is a class of unsupervised data analysis techniques that e...
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12/22/2022
Model Based Co-clustering of Mixed Numerical and Binary Data
Co-clustering is a data mining technique used to extract the underlying ...
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12/20/2022
Pesticide concentration monitoring: investigating spatio-temporal patterns in left censored data
Monitoring pesticide concentration is very important for public authorit...
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12/31/2021
Binary Diffing as a Network Alignment Problem via Belief Propagation
In this paper, we address the problem of finding a correspondence, or ma...
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12/31/2021
Improved Algorithm for the Network Alignment Problem with Application to Binary Diffing
In this paper, we present a novel algorithm to address the Network Align...
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07/15/2021
On the expressivity of bi-Lipschitz normalizing flows
An invertible function is bi-Lipschitz if both the function and its inve...
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02/06/2019
Un modèle Bayésien de co-clustering de données mixtes
We propose a MAP Bayesian approach to perform and evaluate a co-clusteri...
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02/22/2018
The State of the Art in Integrating Machine Learning into Visual Analytics
Visual analytics systems combine machine learning or other analytic tech...
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07/10/2017
Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL
We develop a model in which interactions between nodes of a dynamic netw...
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08/29/2016
Discovering Patterns in Time-Varying Graphs: A Triclustering Approach
This paper introduces a novel technique to track structures in time vary...
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05/09/2016
Mean Absolute Percentage Error for regression models
We study in this paper the consequences of using the Mean Absolute Perce...
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05/09/2016
Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks
The stochastic block model (SBM) is a flexible probabilistic tool that c...
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11/04/2015
Lasso based feature selection for malaria risk exposure prediction
In life sciences, the experts generally use empirical knowledge to recod...
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11/04/2015
Co-Clustering Network-Constrained Trajectory Data
Recently, clustering moving object trajectories kept gaining interest fr...
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11/04/2015
Study of a bias in the offline evaluation of a recommendation algorithm
Recommendation systems have been integrated into the majority of large o...
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10/30/2015
A Study of the Spatio-Temporal Correlations in Mobile Calls Networks
For the last few years, the amount of data has significantly increased i...
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09/09/2015
Sélection de variables par le GLM-Lasso pour la prédiction du risque palustre
In this study, we propose an automatic learning method for variables sel...
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09/08/2015
Empirical risk minimization is consistent with the mean absolute percentage error
We study in this paper the consequences of using the Mean Absolute Perce...
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09/08/2015
Modelling time evolving interactions in networks through a non stationary extension of stochastic block models
In this paper, we focus on the stochastic block model (SBM),a probabilis...
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06/23/2015
Graphs in machine learning: an introduction
Graphs are commonly used to characterise interactions between objects of...
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06/12/2015
Search Strategies for Binary Feature Selection for a Naive Bayes Classifier
We compare in this paper several feature selection methods for the Naive...
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06/12/2015
Using the Mean Absolute Percentage Error for Regression Models
We study in this paper the consequences of using the Mean Absolute Perce...
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06/12/2015
Exact ICL maximization in a non-stationary time extension of the latent block model for dynamic networks
The latent block model (LBM) is a flexible probabilistic tool to describ...
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06/12/2015
Reducing offline evaluation bias of collaborative filtering algorithms
Recommendation systems have been integrated into the majority of large o...
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03/20/2015
Country-scale Exploratory Analysis of Call Detail Records through the Lens of Data Grid Models
Call Detail Records (CDRs) are data recorded by telecommunications compa...
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03/18/2015
Interpretable Aircraft Engine Diagnostic via Expert Indicator Aggregation
Detecting early signs of failures (anomalies) in complex systems is one ...
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07/03/2014
Anomaly Detection Based on Aggregation of Indicators
Automatic anomaly detection is a major issue in various areas. Beyond me...
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07/03/2014
Reducing Offline Evaluation Bias in Recommendation Systems
Recommendation systems have been integrated into the majority of large o...
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07/02/2014
Nonparametric Hierarchical Clustering of Functional Data
In this paper, we deal with the problem of curves clustering. We propose...
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07/02/2014
How Many Dissimilarity/Kernel Self Organizing Map Variants Do We Need?
In numerous applicative contexts, data are too rich and too complex to b...
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02/27/2013
A bag-of-paths framework for network data analysis
This work develops a generic framework, called the bag-of-paths (BoP), f...
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01/12/2013
A Triclustering Approach for Time Evolving Graphs
This paper introduces a novel technique to track structures in time evol...
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10/24/2012
Neural Networks for Complex Data
Artificial neural networks are simple and efficient machine learning too...
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10/02/2012
Graph-Based Approaches to Clustering Network-Constrained Trajectory Data
Even though clustering trajectory data attracted considerable attention ...
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05/10/2012
A Discussion on Parallelization Schemes for Stochastic Vector Quantization Algorithms
This paper studies parallelization schemes for stochastic Vector Quantiz...
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05/10/2012
Modularity-Based Clustering for Network-Constrained Trajectories
We present a novel clustering approach for moving object trajectories th...
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04/29/2012
Dissimilarity Clustering by Hierarchical Multi-Level Refinement
We introduce in this paper a new way of optimizing the natural extension...
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01/04/2012
Clustering Dynamic Web Usage Data
Most classification methods are based on the assumption that data confor...
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01/04/2012
Constrained variable clustering and the best basis problem in functional data analysis
Functional data analysis involves data described by regular functions ra...
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09/07/2010
Optimizing an Organized Modularity Measure for Topographic Graph Clustering: a Deterministic Annealing Approach
This paper proposes an organized generalization of Newman and Girvan's m...
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01/06/2008
Batch kernel SOM and related Laplacian methods for social network analysis
Large graphs are natural mathematical models for describing the structur...
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05/02/2007
Support vector machine for functional data classification
In many applications, input data are sampled functions taking their valu...
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04/01/2006
