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ORCIDIevgen Redko
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2020 – today
- 2024
[c25]Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh:
Breaking isometric ties and introducing priors in Gromov-Wasserstein distances. AISTATS 2024: 298-306- [c24]Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko:
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias. AISTATS 2024: 595-603 - [c23]Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko:
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention. ICML 2024 - [i22]Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko, Jianfeng Zhang, Bo An:
Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift. CoRR abs/2401.08909 (2024) - [i21]Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko:
Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention. CoRR abs/2402.10198 (2024) - [i20]Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko:
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting. CoRR abs/2406.10327 (2024) - [i19]Oussama Zekri, Abdelhakim Benechehab, Ievgen Redko:
Can LLMs predict the convergence of Stochastic Gradient Descent? CoRR abs/2408.01736 (2024) - [i18]Vasilii Feofanov, Romain Ilbert, Malik Tiomoko, Themis Palpanas, Ievgen Redko:
User-friendly Foundation Model Adapters for Multivariate Time Series Classification. CoRR abs/2409.12264 (2024) - 2023
- [j4]Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki:
Learning representations that are closed-form Monge mapping optimal with application to domain adaptation. Trans. Mach. Learn. Res. 2023 (2023) - [c22]Quang Huy Tran, Hicham Janati, Nicolas Courty, Rémi Flamary, Ievgen Redko, Pinar Demetci
, Ritambhara Singh:
Unbalanced CO-optimal Transport. AAAI 2023: 10006-10016 - [c21]Brandon Amos, Giulia Luise, Samuel Cohen, Ievgen Redko:
Meta Optimal Transport. ICML 2023: 791-813 - [i17]Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki:
Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation. CoRR abs/2305.07500 (2023) - [i16]Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh:
Revisiting invariances and introducing priors in Gromov-Wasserstein distances. CoRR abs/2307.10093 (2023) - [i15]Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski:
Understanding deep neural networks through the lens of their non-linearity. CoRR abs/2310.11439 (2023) - [i14]Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko:
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias. CoRR abs/2310.14814 (2023) - 2022
- [c20]Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard:
Improving Few-Shot Learning Through Multi-task Representation Learning Theory. ECCV (20) 2022: 435-452 - [c19]Rehan Jhuboo, Ievgen Redko, Alain Guignandon, Françoise Peyrin, Marc Sebban:
Why do State-of-the-art Super-Resolution Methods not work well for Bone Microstructure CT Imaging? EUSIPCO 2022: 1283-1287 - [i13]Quang Huy Tran, Hicham Janati, Nicolas Courty, Rémi Flamary, Ievgen Redko, Pinar Demetci, Ritambhara Singh:
Unbalanced CO-Optimal Transport. CoRR abs/2205.14923 (2022) - [i12]Brandon Amos, Samuel Cohen, Giulia Luise, Ievgen Redko:
Meta Optimal Transport. CoRR abs/2206.05262 (2022) - 2021
- [j3]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:
POT: Python Optimal Transport. J. Mach. Learn. Res. 22: 78:1-78:8 (2021) - [c18]Nina Vesseron, Ievgen Redko, Charlotte Laclau:
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond. AISTATS 2021: 1765-1773 - [c17]Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron:
All of the Fairness for Edge Prediction with Optimal Transport. AISTATS 2021: 1774-1782 - [i11]Quang Huy Tran, Hicham Janati, Ievgen Redko, Rémi Flamary, Nicolas Courty:
Factored couplings in multi-marginal optimal transport via difference of convex programming. CoRR abs/2110.00629 (2021) - 2020
- [c16]Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban:
A Swiss Army Knife for Minimax Optimal Transport. ICML 2020: 2504-2513 - [c15]Sofien Dhouib, Ievgen Redko, Carole Lartizien:
Margin-aware Adversarial Domain Adaptation with Optimal Transport. ICML 2020: 2514-2524 - [c14]Titouan Vayer, Ievgen Redko, Rémi Flamary, Nicolas Courty:
CO-Optimal Transport. NeurIPS 2020 - [i10]Ievgen Redko, Titouan Vayer, Rémi Flamary, Nicolas Courty:
CO-Optimal Transport. CoRR abs/2002.03731 (2020) - [i9]Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani:
A survey on domain adaptation theory. CoRR abs/2004.11829 (2020) - [i8]Charlotte Laclau, Franck Iutzeler, Ievgen Redko:
Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy. CoRR abs/2009.00365 (2020) - [i7]Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard:
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms. CoRR abs/2010.01992 (2020) - [i6]Nina Vesseron, Ievgen Redko, Charlotte Laclau:
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond. CoRR abs/2010.11024 (2020) - [i5]Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron:
All of the Fairness for Edge Prediction with Optimal Transport. CoRR abs/2010.16326 (2020)
2010 – 2019
- 2019
- [j2]Ievgen Redko, Amaury Habrard, Marc Sebban:
On the analysis of adaptability in multi-source domain adaptation. Mach. Learn. 108(8-9): 1635-1652 (2019) - [c13]Ievgen Redko, Charlotte Laclau:
On Fair Cost Sharing Games in Machine Learning. AAAI 2019: 4790-4797 - [c12]Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia:
Optimal Transport for Multi-source Domain Adaptation under Target Shift. AISTATS 2019: 849-858 - 2018
- [c11]Georgios Balikas, Charlotte Laclau, Ievgen Redko, Massih-Reza Amini:
Cross-Lingual Document Retrieval Using Regularized Wasserstein Distance. ECIR 2018: 398-410 - [c10]Sofiane Dhouib, Ievgen Redko:
Revisiting (\epsilon, \gamma, \tau)-similarity learning for domain adaptation. NeurIPS 2018: 7408-7417 - [c9]Léo Gautheron, Ievgen Redko, Carole Lartizien:
Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport. ECML/PKDD (2) 2018: 759-776 - [c8]Qi Wang, Ievgen Redko, Sylvain Takerkart:
Population Averaging of Neuroimaging Data Using Lp Distance-based Optimal Transport. PRNI 2018: 1-4 - [i4]Georgios Balikas, Charlotte Laclau, Ievgen Redko, Massih-Reza Amini:
Cross-lingual Document Retrieval using Regularized Wasserstein Distance. CoRR abs/1805.04437 (2018) - [i3]Léo Gautheron, Ievgen Redko, Carole Lartizien:
Feature Selection for Unsupervised Domain Adaptation using Optimal Transport. CoRR abs/1806.10861 (2018) - 2017
- [c7]Charlotte Laclau, Ievgen Redko, Basarab Matei, Younès Bennani, Vincent Brault:
Co-clustering through Optimal Transport. ICML 2017: 1955-1964 - [c6]Ievgen Redko, Amaury Habrard, Marc Sebban:
Theoretical Analysis of Domain Adaptation with Optimal Transport. ECML/PKDD (2) 2017: 737-753 - 2016
- [j1]Ievgen Redko, Younès Bennani:
Non-negative embedding for fully unsupervised domain adaptation. Pattern Recognit. Lett. 77: 35-41 (2016) - [c5]Ievgen Redko, Younès Bennani:
Kernel alignment for unsupervised transfer learning. ICPR 2016: 525-530 - [i2]Ievgen Redko, Amaury Habrard, Marc Sebban:
Theoretical Analysis of Domain Adaptation with Optimal Transport. CoRR abs/1610.04420 (2016) - [i1]Ievgen Redko, Younès Bennani:
Kernel Alignment for Unsupervised Transfer Learning. CoRR abs/1610.06434 (2016) - 2015
- [c4]Ievgen Redko, Younès Bennani:
Sparsity analysis of learned factors in Multilayer NMF. IJCNN 2015: 1-7 - 2014
- [c3]Ievgen Redko, Younès Bennani:
Non-negative Matrix Factorization with Schatten p-norms Reguralization. ICONIP (2) 2014: 52-59 - [c2]Ievgen Redko, Younès Bennani:
Controlling orthogonality constraints for better NMF clustering. IJCNN 2014: 3894-3900 - [c1]Ievgen Redko, Younès Bennani:
Random subspaces NMF for unsupervised transfer learning. IJCNN 2014: 3901-3908
Coauthor Index
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last updated on 2024-10-18 19:32 CEST by the dblp team
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