← Authors

Ievgen Redko

19 papers · 2017–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) πŸ—ΊοΈ Taxonomy Completionist (23) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (8) πŸ† Grand Slam πŸ‘₯ Mega-Team (22) πŸ”₯ Unstoppable (9) πŸ’Ž Century Club (19) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (60)

Conferences

AISTATS (5) ICML (5) NIPS (3) AAAI (2) CVPR (1) ECCV (1) ICLR (1) JMLR (1)

Top co-authors

Charlotte Laclau (5) RΓ©mi Flamary (4) Ambroise Odonnat (4) Nicolas Courty (4) Vasilii Feofanov (3) Themis Palpanas (2) Quang Huy TRAN (2) Pinar Demetci (2) Quentin Bouniot (2) Hicham Janati (2)

Keywords

optimal transport (11) domain adaptation (5) gromov-wasserstein distance (3) feature alignment (3) wasserstein distance (2) target domain (2) distribution matching (2) game theory (2) variational inference (1) hyperparameter optimization (1) algorithmic fairness (1) similarity learning (1) loss landscape (1) minimax optimization (1) time series forecasting (1) robust optimization (1) probability distribution (1) nash equilibrium (1) feature correspondence (1) transfer learning (1)

Papers

Zero-shot Model-based Reinforcement Learning using Large Language Models ICLR 2025
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport CVPR 2025
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias AISTATS 2024
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention ICML 2024
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting NIPS 2024
Breaking isometric ties and introducing priors in Gromov-Wasserstein distances AISTATS 2024
Meta Optimal Transport ICML 2023
Unbalanced CO-optimal Transport AAAI 2023
Improving Few-Shot Learning through Multi-task Representation Learning Theory ECCV 2022
POT: Python Optimal Transport JMLR 2021
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond AISTATS 2021
All of the Fairness for Edge Prediction with Optimal Transport AISTATS 2021
Margin-aware Adversarial Domain Adaptation with Optimal Transport ICML 2020
A Swiss Army Knife for Minimax Optimal Transport ICML 2020
CO-Optimal Transport NIPS 2020
Optimal Transport for Multi-source Domain Adaptation under Target Shift AISTATS 2019
On Fair Cost Sharing Games in Machine Learning AAAI 2019
Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation NIPS 2018
Co-clustering through Optimal Transport ICML 2017