Ievgen Redko

Orcid: 0000-0002-3860-5502

According to our database1, Ievgen Redko authored at least 35 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.
CoRR, 2024

Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift.
CoRR, 2024

2023
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias.
CoRR, 2023

Understanding deep neural networks through the lens of their non-linearity.
CoRR, 2023

Revisiting invariances and introducing priors in Gromov-Wasserstein distances.
CoRR, 2023

Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation.
CoRR, 2023

Meta Optimal Transport.
Proceedings of the International Conference on Machine Learning, 2023

Unbalanced CO-optimal Transport.
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?
Proceedings of the 30th European Signal Processing Conference, 2022

Improving Few-Shot Learning Through Multi-task Representation Learning Theory.
Proceedings of the Computer Vision - ECCV 2022, 2022

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

Factored couplings in multi-marginal optimal transport via difference of convex programming.
CoRR, 2021

Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

All of the Fairness for Edge Prediction with Optimal Transport.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms.
CoRR, 2020

Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy.
CoRR, 2020

A survey on domain adaptation theory.
CoRR, 2020

CO-Optimal Transport.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Swiss Army Knife for Minimax Optimal Transport.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
On the analysis of adaptability in multi-source domain adaptation.
Mach. Learn., 2019

Optimal Transport for Multi-source Domain Adaptation under Target Shift.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Fair Cost Sharing Games in Machine Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Population Averaging of Neuroimaging Data Using L<sup>p</sup> Distance-based Optimal Transport.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Revisiting (\epsilon, \gamma, \tau)-similarity learning for domain adaptation.
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.
Proceedings of the Advances in Information Retrieval, 2018

2017
Theoretical Analysis of Domain Adaptation with Optimal Transport.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Co-clustering through Optimal Transport.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Non-negative embedding for fully unsupervised domain adaptation.
Pattern Recognit. Lett., 2016

Kernel alignment for unsupervised transfer learning.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015
Sparsity analysis of learned factors in Multilayer NMF.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Random subspaces NMF for unsupervised transfer learning.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Controlling orthogonality constraints for better NMF clustering.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Non-negative Matrix Factorization with Schatten p-norms Reguralization.
Proceedings of the Neural Information Processing - 21st International Conference, 2014


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