Ievgen Redko

According to our database, Ievgen Redko authored at least 43 papers between 2014 and 2024.

Collaborative distances:

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

2024

Zero-shot Model-based Reinforcement Learning using Large Language Models.

Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl

CoRR, 2024

Large Language Models as Markov Chains.

Oussama Zekri, Ambroise Odonnat, Abdelhakim Benechehab, Linus Bleistein, Nicolas Boullé, Ievgen Redko

CoRR, 2024

User-friendly Foundation Model Adapters for Multivariate Time Series Classification.

Vasilii Feofanov, Romain Ilbert, Malik Tiomoko, Themis Palpanas, Ievgen Redko

CoRR, 2024

Can LLMs predict the convergence of Stochastic Gradient Descent?

Oussama Zekri, Abdelhakim Benechehab, Ievgen Redko

CoRR, 2024

Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting.

Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko

CoRR, 2024

Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

CoRR, 2024

Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift.

Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko, Jianfeng Zhang, Bo An

CoRR, 2024

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias.

Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Breaking isometric ties and introducing priors in Gromov-Wasserstein distances.

Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Learning representations that are closed-form Monge mapping optimal with application to domain adaptation.

Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki

Trans. Mach. Learn. Res., 2023

Understanding deep neural networks through the lens of their non-linearity.

Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski

CoRR, 2023

Revisiting invariances and introducing priors in Gromov-Wasserstein distances.

Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh

CoRR, 2023

Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation.

Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki

CoRR, 2023

Meta Optimal Transport.

Brandon Amos, Giulia Luise, Samuel Cohen, Ievgen Redko

Proceedings of the International Conference on Machine Learning, 2023

Unbalanced CO-optimal Transport.

Quang Huy Tran, Hicham Janati, Nicolas Courty, Rémi Flamary, Ievgen Redko, Pinar Demetci, Ritambhara Singh

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Why do State-of-the-art Super-Resolution Methods not work well for Bone Microstructure CT Imaging?

Rehan Jhuboo, Ievgen Redko, Alain Guignandon, Françoise Peyrin, Marc Sebban

Proceedings of the 30th European Signal Processing Conference, 2022

Improving Few-Shot Learning Through Multi-task Representation Learning Theory.

Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

POT: Python Optimal Transport.

Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

J. Mach. Learn. Res., 2021

Factored couplings in multi-marginal optimal transport via difference of convex programming.

Quang Huy Tran, Hicham Janati, Ievgen Redko, Rémi Flamary, Nicolas Courty

CoRR, 2021

Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond.

Nina Vesseron, Ievgen Redko, Charlotte Laclau

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

All of the Fairness for Edge Prediction with Optimal Transport.

Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms.

Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard

CoRR, 2020

Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy.

Charlotte Laclau, Franck Iutzeler, Ievgen Redko

CoRR, 2020

A survey on domain adaptation theory.

Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani

CoRR, 2020

CO-Optimal Transport.

Titouan Vayer, Ievgen Redko, Rémi Flamary, Nicolas Courty

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Margin-aware Adversarial Domain Adaptation with Optimal Transport.

Sofien Dhouib, Ievgen Redko, Carole Lartizien

Proceedings of the 37th International Conference on Machine Learning, 2020

A Swiss Army Knife for Minimax Optimal Transport.

Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

On the analysis of adaptability in multi-source domain adaptation.

Ievgen Redko, Amaury Habrard, Marc Sebban

Mach. Learn., 2019

Optimal Transport for Multi-source Domain Adaptation under Target Shift.

Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Fair Cost Sharing Games in Machine Learning.

Ievgen Redko, Charlotte Laclau

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Population Averaging of Neuroimaging Data Using L^p Distance-based Optimal Transport.

Qi Wang, Ievgen Redko, Sylvain Takerkart

Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport.

Léo Gautheron, Ievgen Redko, Carole Lartizien

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Revisiting (\epsilon, \gamma, \tau)-similarity learning for domain adaptation.

Sofiane Dhouib, Ievgen Redko

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Cross-Lingual Document Retrieval Using Regularized Wasserstein Distance.

Georgios Balikas, Charlotte Laclau, Ievgen Redko, Massih-Reza Amini

Proceedings of the Advances in Information Retrieval, 2018

2017

Theoretical Analysis of Domain Adaptation with Optimal Transport.

Ievgen Redko, Amaury Habrard, Marc Sebban

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Co-clustering through Optimal Transport.

Charlotte Laclau, Ievgen Redko, Basarab Matei, Younès Bennani, Vincent Brault

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Non-negative embedding for fully unsupervised domain adaptation.

Ievgen Redko, Younès Bennani

Pattern Recognit. Lett., 2016

Kernel alignment for unsupervised transfer learning.

Ievgen Redko, Younès Bennani

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015

Sparsity analysis of learned factors in Multilayer NMF.

Ievgen Redko, Younès Bennani

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

2014

Random subspaces NMF for unsupervised transfer learning.

Ievgen Redko, Younès Bennani

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Controlling orthogonality constraints for better NMF clustering.

Ievgen Redko, Younès Bennani

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Non-negative Matrix Factorization with Schatten p-norms Reguralization.

Ievgen Redko, Younès Bennani

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