Alain Rakotomamonjy

Orcid: 0000-0002-4210-7792

According to our database1, Alain Rakotomamonjy authored at least 114 papers between 2002 and 2024.

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Bibliography

2024
Personalised Federated Learning On Heterogeneous Feature Spaces.
Trans. Mach. Learn. Res., 2024

Improving Consistency Models with Generator-Induced Coupling.
CoRR, 2024

Gaussian-Smoothed Sliced Probability Divergences.
CoRR, 2024

Open Research Challenges for Private Advertising Systems Under Local Differential Privacy.
Proceedings of the Web Information Systems Engineering - WISE 2024, 2024

Federated Wasserstein Distance.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Approximating dynamic time warping with a convolutional neural network on EEG data.
Pattern Recognit. Lett., 2023

Differentially Private Gradient Flow based on the Sliced Wasserstein Distance for Non-Parametric Generative Modeling.
CoRR, 2023

Approximating DTW with a convolutional neural network on EEG data.
CoRR, 2023

Adversarial Sample Detection Through Neural Network Transport Dynamics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Unifying GANs and Score-Based Diffusion as Generative Particle Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning an autoencoder to compress EEG signals via a neural network based approximation of DTW.
Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances.
Proceedings of the International Conference on Machine Learning, 2023

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals.
Proceedings of the International Conference on Machine Learning, 2023

Continuous PDE Dynamics Forecasting with Implicit Neural Representations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Optimal transport for conditional domain matching and label shift.
Mach. Learn., 2022

Theoretical guarantees for bridging metric measure embedding and optimal transport.
Neurocomputing, 2022

Multi-source domain adaptation via weighted joint distributions optimal transport.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Diverse Weight Averaging for Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Benchopt: Reproducible, efficient and collaborative optimization benchmarks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalizing to New Physical Systems via Context-Informed Dynamics Model.
Proceedings of the International Conference on Machine Learning, 2022

Mapping conditional distributions for domain adaptation under generalized target shift.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Integrating Isolated Examples with Weakly-Supervised Sound Event Detection: A Direct Approach.
Proceedings of the 7th Workshop on Detection and Classification of Acoustic Scenes and Events 2022, 2022

Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
POT: Python Optimal Transport.
J. Mach. Learn. Res., 2021

Unsupervised domain adaptation with non-stochastic missing data.
Data Min. Knowl. Discov., 2021

Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences.
CoRR, 2021

Distributional Sliced Embedding Discrepancy for Incomparable Distributions.
CoRR, 2021

Photonic Differential Privacy with Direct Feedback Alignment.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Sliced Wasserstein Distance.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Wasserstein Learning of Determinantal Point Processes.
CoRR, 2020

Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression.
CoRR, 2020

Match and Reweight Strategy for Generalized Target Shift.
CoRR, 2020

Non-Aligned Distribution Distance using Metric Measure Embedding and Optimal Transport.
CoRR, 2020

Partial Trace Regression and Low-Rank Kraus Decomposition.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Online multimodal dictionary learning.
Neurocomputing, 2019

Singleshot : a scalable Tucker tensor decomposition.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Screening Sinkhorn Algorithm for Regularized Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Screening rules for Lasso with non-convex Sparse Regularizers.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Wasserstein discriminant analysis.
Mach. Learn., 2018

Wasserstein Distance Measure Machines.
CoRR, 2018

Concave Losses for Robust Dictionary Learning.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Non-Negative Tensor Dictionary Learning.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization.
IEEE Trans. Neural Networks Learn. Syst., 2017

Editorial: A Successful Year and Looking Forward to 2017 and Beyond.
IEEE Trans. Neural Networks Learn. Syst., 2017

Supervised Representation Learning for Audio Scene Classification.
IEEE ACM Trans. Audio Speech Lang. Process., 2017

Optimal Transport for Domain Adaptation.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Joint distribution optimal transportation for domain adaptation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Optimal transport Applied to Transfer Learning for P300 Detection.
Proceedings of the From Vision to Reality, 2017

2016
DC Proximal Newton for Nonconvex Optimization Problems.
IEEE Trans. Neural Networks Learn. Syst., 2016

Operator-valued Kernels for Learning from Functional Response Data.
J. Mach. Learn. Res., 2016

Early and Reliable Event Detection Using Proximity Space Representation.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Histogram of Gradients of Time-Frequency Representations for Audio Scene Classification.
IEEE ACM Trans. Audio Speech Lang. Process., 2015

Filter bank learning for signal classification.
Signal Process., 2015

Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization.
CoRR, 2015

Histogram of gradients of Time-Frequency Representations for Audio scene detection.
CoRR, 2015

DC Proximal Newton for Non-Convex Optimization Problems.
CoRR, 2015

Generalized conditional gradient: analysis of convergence and applications.
CoRR, 2015

Early frame-based detection of acoustic scenes.
Proceedings of the 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2015

Multitemporal classification without new labels: A solution with optimal transport.
Proceedings of the 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2015

More efficient sparsity-inducing algorithms using inexact gradient.
Proceedings of the 23rd European Signal Processing Conference, 2015

Importance sampling strategy for non-convex randomized block-coordinate descent.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM.
IEEE Trans. Geosci. Remote. Sens., 2014

ℓ<sub>p</sub>-norm multiple kernel learning with low-rank kernels.
Neurocomputing, 2014

Mixed-Norm Regularization for Brain Decoding.
Comput. Math. Methods Medicine, 2014

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images.
Artif. Intell. Medicine, 2014

Kernel learning as minimization of the single validation estimate.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Active set strategy for high-dimensional non-convex sparse optimization problems.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Direct Optimization of the Dictionary Learning Problem.
IEEE Trans. Signal Process., 2013

Learning with infinitely many features.
Mach. Learn., 2013

Applying alternating direction method of multipliers for constrained dictionary learning.
Neurocomputing, 2013

Functional Regularized Least Squares Classi cation with Operator-valued Kernels
CoRR, 2013

Create the relevant spatial filterbank in the hyperspectral jungle.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

Filter bank Kernel Learning for nonstationary signal classification.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Large Margin Filtering.
IEEE Trans. Signal Process., 2012

Multiple Operator-valued Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Discovering relevant spatial filterbanks for VHR image classification.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Adaptive Canonical Correlation Analysis Based On Matrix Manifolds.
Proceedings of the 29th International Conference on Machine Learning, 2012

Sparse Support Vector Infinite Push.
Proceedings of the 29th International Conference on Machine Learning, 2012

Oblique principal subspace tracking on manifold.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
ell<sub>p</sub>-ell<sub>q</sub> Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning.
IEEE Trans. Neural Networks, 2011

Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms.
Signal Process., 2011

Apprentissage de dictionnaires d'ondelettes vaste marge pour la classification de signaux et de textures.
Rev. d'Intelligence Artif., 2011

Wavelet kernel learning.
Pattern Recognit., 2011

Decoding finger movements from ECoG signals using switching linear models
CoRR, 2011

Functional Regularized Least Squares Classication with Operator-valued Kernels.
Proceedings of the 28th International Conference on Machine Learning, 2011

A supervised strategy for deep kernel machine.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Selecting from an infinite set of features in SVM.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

2010
Composite kernel learning.
Mach. Learn., 2010

Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signaux
CoRR, 2010

Large marginwavelet-based dictionary for signal classification.
Proceedings of the IEEE International Conference on Acoustics, 2010

Large margin filtering for Signal Sequence Labeling.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Recovering sparse signals with a certain family of nonconvex penalties and DC programming.
IEEE Trans. Signal Process., 2009

2008
BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller.
IEEE Trans. Biomed. Eng., 2008

Support Vector Machines with a Reject Option.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Analysis of SVM regression bounds for variable ranking.
Neurocomputing, 2007

A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier.
Proceedings of the IEEE Intelligent Transportation Systems Conference, 2007

More efficiency in multiple kernel learning.
Proceedings of the Machine Learning, 2007

Kernel on Bag of Paths For Measuring Similarity of Shapes.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

One-class SVM regularization path and comparison with alpha seeding.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006
Perception d'états affectifs et apprentissage.
Rev. d'Intelligence Artif., 2006

Kernel Basis Pursuit.
Rev. d'Intelligence Artif., 2006

Translation-invariant classification of non-stationary signals.
Neurocomputing, 2006

Object Categorization Using Kernels Combining Graphs and Histograms of Gradients.
Proceedings of the Image Analysis and Recognition, Third International Conference, 2006

2005
Frames, Reproducing Kernels, Regularization and Learning.
J. Mach. Learn. Res., 2005

Segmentation Evaluation Using a Support Vector Machine.
Proceedings of the Pattern Recognition and Data Mining, 2005

Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances.
Proceedings of the Artificial Neural Networks: Biological Inspirations, 2005

Evaluation of the quality of ultrasound image compression by fusion of criteria with a support vector machine.
Proceedings of the 13th European Signal Processing Conference, 2005

2004
Optimizing Area Under Roc Curve with SVMs.
Proceedings of the ROC Analysis in Artificial Intelligence, 1st International Workshop, 2004

Generic target recognition.
Proceedings of the 2004 12th European Signal Processing Conference, 2004

2003
Variable Selection Using SVM-based Criteria.
J. Mach. Learn. Res., 2003

2002
Comparaison de stratégies de discrimination de masses de véhicules automobiles.
Rev. d'Intelligence Artif., 2002

Frame Kernels for Learning.
Proceedings of the Artificial Neural Networks, 2002


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