Alexis Bondu

According to our database, Alexis Bondu authored at least 41 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols

Mach. Learn., December, 2023

biquality-learn: a Python library for Biquality Learning.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols

CoRR, 2023

Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion.

Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Open challenges for Machine Learning based Early Decision-Making research.

Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-Francois Marteau

SIGKDD Explor., 2022

ECOTS: Early Classification in Open Time Series.

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire

CoRR, 2022

Early and Revocable Time Series Classification.

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire

Proceedings of the International Joint Conference on Neural Networks, 2022

Repondération Préférentielle pour l'Apprentissage Biqualité.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols

Proceedings of the Extraction et Gestion des Connaissances, 2022

When to Classify Events in Open Times Series?

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Early classification of time series.

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Asma Dachraoui

Mach. Learn., 2021

Early Classification of Time Series is Meaningful.

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire

CoRR, 2021

Contrastive Representations for Label Noise Require Fine-Tuning.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols

Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), 2021

Interpretable Feature Construction for Time Series Extrinsic Regression.

Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

From Weakly Supervised Learning to Biquality Learning: an Introduction.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou

Proceedings of the International Joint Conference on Neural Networks, 2021

Importance Reweighting for Biquality Learning.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou

Proceedings of the International Joint Conference on Neural Networks, 2021

Early Classification of Time Series: Cost-based multiclass Algorithms.

Paul-Emile Zafar, Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire

Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

2020

From Weakly Supervised Learning to Biquality Learning, a brief introduction.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou

CoRR, 2020

Importance Reweighting for Biquality Learning.

Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols

CoRR, 2020

Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms.

Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Asma Dachraoui

CoRR, 2020

Sélections simultanées de variables et de représentations pour la classification de séries temporelles.

Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka

Proceedings of the Extraction et Gestion des Connaissances, 2020

Multivariate Time Series Classification: A Relational Way.

Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot

Proceedings of the Big Data Analytics and Knowledge Discovery, 2020

2019

Proactive Fiber Break Detection Based on Quaternion Time Series and Automatic Variable Selection from Relational Data.

Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot, Fabrice Clérot

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2019

Toward a Framework for Seasonal Time Series Forecasting Using Clustering.

Colin Leverger, Simon Malinowski, Thomas Guyet, Vincent Lemaire, Alexis Bondu, Alexandre Termier

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

FEARS: a Feature and Representation Selection approach for Time Series Classification.

Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2015

Early Classification of Time Series as a Non Myopic Sequential Decision Making Problem.

Asma Dachraoui, Alexis Bondu, Antoine Cornuéjols

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization.

Alexis Bondu, Marc Boullé, Antoine Cornuéjols

Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, 2015

Realistic and very fast simulation of individual electricity consumptions.

Alexis Bondu, Asma Dachraoui

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Evaluation Protocol of Early Classifiers over Multiple Data Sets.

Asma Dachraoui, Alexis Bondu, Antoine Cornuéjols

Proceedings of the Neural Information Processing - 21st International Conference, 2014

A Survey on Supervised Classification on Data Streams.

Vincent Lemaire, Christophe Salperwyck, Alexis Bondu

Proceedings of the Business Intelligence - 4th European Summer School, 2014

2013

SAXO: An optimized data-driven symbolic representation of time series.

Alexis Bondu, Marc Boullé, Benoît Grossin

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2011

A supervised approach for change detection in data streams.

Alexis Bondu, Marc Boullé

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Détection de changements de distribution dans un flux de données : une approche supervisée.

Alexis Bondu, Marc Boullé

Proceedings of the Extraction et gestion des connaissances (EGC'2011), 2011

2010

A non-parametric semi-supervised discretization method.

Alexis Bondu, Marc Boullé, Vincent Lemaire

Knowl. Inf. Syst., 2010

Exploration vs. exploitation in active learning : A Bayesian approach.

Alexis Bondu, Vincent Lemaire, Marc Boullé

Proceedings of the International Joint Conference on Neural Networks, 2010

Une nouvelle stratégie d'apprentissage Bayésienne.

Alexis Bondu, Vincent Lemaire, Marc Boullé

Proceedings of the Extraction et gestion des connaissances (EGC'2010), 2010

Density estimation on data stream : an application to change detection.

Alexis Bondu, Benoît Grossin, Marie-Luce Picard

Proceedings of the Extraction et gestion des connaissances (EGC'2010), 2010

2008

Apprentissage actif par modèles locaux. (Active learning using local models).

Alexis Bondu

PhD thesis, 2008

Adaptive curiosity for emotions detection in speech.

Alexis Bondu, Vincent Lemaire

Proceedings of the International Joint Conference on Neural Networks, 2008

A Non-parametric Semi-supervised Discretization Method.

Alexis Bondu, Marc Boullé, Vincent Lemaire, Stéphane Loiseau, Béatrice Duval

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

Active Learning Strategies: A Case Study for Detection of Emotions in Speech.

Alexis Bondu, Vincent Lemaire, Barbara Poulain

Proceedings of the Advances in Data Mining. Theoretical Aspects and Applications, 2007

Apprentissage actif d'émotions dans les dialogues Homme-Machine.

Alexis Bondu, Vincent Lemaire, Barbara Poulain

Proceedings of the Extraction et gestion des connaissances (EGC'2007), 2007

2006

État de l'art sur les méthodes statistiques d'apprentissage actif.

Alexis Bondu, Vincent Lemaire

Proceedings of the Apprentissage Artificiel et Fouille de Données, 2006