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Ievgen 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 - [i24]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) - [i23]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) - [i22]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) - [i21]Oussama Zekri, Abdelhakim Benechehab, Ievgen Redko:
Can LLMs predict the convergence of Stochastic Gradient Descent? CoRR abs/2408.01736 (2024) - [i20]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) - [i19]Oussama Zekri, Ambroise Odonnat, Abdelhakim Benechehab, Linus Bleistein, Nicolas Boullé, Ievgen Redko:
Large Language Models as Markov Chains. CoRR abs/2410.02724 (2024) - [i18]Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl:
Zero-shot Model-based Reinforcement Learning using Large Language Models. CoRR abs/2410.11711 (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
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
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
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
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
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 2024-12-01 00:17 CET by the dblp team
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