Ievgen Redko
19 papers · 2017–2025 · 8 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (26) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
👥
Mega-Team · Squad
🏆
Grand Slam
🚀
Conference Pioneer
💎
Century Club · Bronze
🗃️
Keyword Collector
(70)
🔥
Unstoppable · Bronze
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(12)
Application Areas
(8)
Artificial Intelligence
(6)
Mathematics & Optimization
(6)
Core Methods
(6)
Optimization
(6)
Core AI
(4)
Deep Learning
(3)
Learning Types · Machine Learning
(3)
Data Science & Analytics
(2)
Architectures
(2)
Learning Paradigms
(2)
Applications
(1)
Learning Types · Deep Learning
(1)
Keywords
optimal transport
(11)
domain adaptation
(5)
gromov-wasserstein distance
(3)
feature alignment
(3)
wasserstein distance
(2)
game theory
(2)
multivariate time series
(2)
distribution matching
(2)
target domain
(2)
robust optimization
(1)
similarity learning
(1)
adversarial learning
(1)
hyperparameter optimization
(1)
transfer learning
(1)
metric learning
(1)
loss landscape
(1)
sharpness-aware minimization
(1)
variational inference
(1)
minimax optimization
(1)
transformer
(1)
Papers
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
CVPR 2025
Zero-shot Model-based Reinforcement Learning using Large Language Models
ICLR 2025
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
NeurIPS 2024
Breaking isometric ties and introducing priors in Gromov-Wasserstein distances
AISTATS 2024
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
Meta Optimal Transport
ICML 2023
Unbalanced CO-optimal Transport
AAAI 2023
Improving Few-Shot Learning through Multi-task Representation Learning Theory
ECCV 2022
All of the Fairness for Edge Prediction with Optimal Transport
AISTATS 2021
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
AISTATS 2021
POT: Python Optimal Transport
JMLR 2021
A Swiss Army Knife for Minimax Optimal Transport
ICML 2020
CO-Optimal Transport
NeurIPS 2020
Margin-aware Adversarial Domain Adaptation with Optimal Transport
ICML 2020
On Fair Cost Sharing Games in Machine Learning
AAAI 2019
Optimal Transport for Multi-source Domain Adaptation under Target Shift
AISTATS 2019
Revisiting (ε, γ, τ)-similarity learning for domain adaptation
NeurIPS 2018
Co-clustering through Optimal Transport
ICML 2017