Ievgen Redko
Ievgen Redko
Associate professor, Hubert Curien laboratory, University of Jean Monnet
Vahvistettu sähköpostiosoite verkkotunnuksessa univ-st-etienne.fr - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Theoretical Analysis of Domain Adaptation with Optimal Transport
I Redko, A Habrard, M Sebban
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
532017
Optimal transport for multi-source domain adaptation under target shift
I Redko, N Courty, R Flamary, D Tuia
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
442019
Advances in Domain Adaptation Theory
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
Elsevier, 2019
212019
Co-clustering through optimal transport
C Laclau, I Redko, B Matei, Y Bennani, V Brault
ICML'17, 2017
182017
Non-negative embedding for fully unsupervised domain adaptation
I Redko, Y Bennani
Pattern Recognition Letters 77, 35-41, 2016
102016
A survey on domain adaptation theory: learning bounds and theoretical guarantees
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
arXiv preprint arXiv:2004.11829, 2020
92020
Feature Selection for Unsupervised Domain Adaptation using Optimal Transport
L Gautheron, I Redko, C Lartizien
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
92018
Cross-Lingual Document Retrieval Using Regularized Wasserstein Distance
G Balikas, C Laclau, I Redko, MR Amini
European Conference on Information Retrieval, 398-410, 2018
82018
Random subspaces NMF for unsupervised transfer learning
I Redko, Y Bennani
2014 International Joint Conference on Neural Networks (IJCNN), 3901-3908, 2014
62014
Controlling orthogonality constraints for better NMF clustering
I Redko, Y Bennani
2014 International Joint Conference on Neural Networks (IJCNN), 3894-3900, 2014
52014
On the analysis of adaptability in multi-source domain adaptation
I Redko, A Habrard, M Sebban
Machine Learning 108 (8), 1635-1652, 2019
42019
CO-Optimal Transport
V Titouan, I Redko, R Flamary, N Courty
Advances in Neural Information Processing Systems 33, 2020
3*2020
A Swiss Army Knife for Minimax Optimal Transport
S Dhouib, I Redko, T Kerdoncuff, R Emonet, M Sebban
Thirty-seventh International Conference on Machine Learning, 2020
22020
Revisiting (ε, γ, τ)-similarity learning for domain adaptation
S Dhouib, I Redko
NeurIPS 2018, 2018
22018
Kernel alignment for unsupervised transfer learning
I Redko, Y Bennani
2016 23rd International Conference on Pattern Recognition (ICPR), 525-530, 2016
22016
Sparsity analysis of learned factors in Multilayer NMF
I Redko, Y Bennani
2015 International Joint Conference on Neural Networks (IJCNN), 1-7, 2015
22015
Margin-aware Adversarial Domain Adaptation with Optimal Transport
S Dhouib, I Redko, C Lartizien
Thirty-seventh International Conference on Machine Learning, 2020
12020
On Fair Cost Sharing Games in Machine Learning
I Redko, C Laclau
AAAI Conference on Artificial Intelligence, 2019
12019
All of the Fairness for Edge Prediction with Optimal Transport
C Laclau, I Redko, M Choudhary, C Largeron
arXiv preprint arXiv:2010.16326, 2020
2020
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
N Vesseron, I Redko, C Laclau
arXiv preprint arXiv:2010.11024, 2020
2020
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Artikkelit 1–20