mlsanityData to 14 Oct 2026

Joint Distribution Optimal Transportation for Domain Adaptation

arXiv 1705.08848 ↗First posted 24 May 2017stat.ML cs.LGcited by 282

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Abstract (arXiv)

This paper deals with the unsupervised domain adaptation problem, where one wants to estimate a prediction function f in a given target domain without any labeled sample by exploiting the knowledge available from a source domain where labels are known. Our work makes the following assumption: there exists a non-linear transformation between the joint feature/label space distributions of the two domain Ps and Pt. We propose a solution of this problem with optimal transport, that allows to recover an estimated target Pft=(X,f(X)) by optimizing simultaneously the optimal coupling and f. We show that our method corresponds to the minimization of a bound on the target error, and provide an efficient algorithmic solution, for which convergence is proved. The versatility of our approach, both in terms of class of hypothesis or loss functions is demonstrated with real world classification and regression problems, for which we reach or surpass state-of-the-art results.

Key facts. Cited by 282 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 May 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 44; 2022: 46; 2023: 62; 2024: 51; 2025: 41; 2026: 38.

282 papers.

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  1. 2023Diffusion Schr"odinger Bridge Matchingcited by 153
  2. 2021Unbalanced minibatch Optimal Transport; applications to Domain Adaptationcited by 125
  3. 2021Predicting with Confidence on Unseen Distributionscited by 116
  4. 2022Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectivescited by 98
  5. 2021Domain Impression: A Source Data Free Domain Adaptation Methodcited by 91
  6. 2023LAVA: Data Valuation without Pre-Specified Learning Algorithmscited by 69
  7. 2023Recent Advances in Optimal Transport for Machine Learningcited by 66
  8. 2021A Prototype-Oriented Framework for Unsupervised Domain Adaptationcited by 62
  9. 2023Domain Adaptation for Time Series Under Feature and Label Shiftscited by 60
  10. 2022Transferability in Deep Learning: A Surveycited by 57
  11. 2023Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspectivecited by 54
  12. 2021Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projectionscited by 53
38 more
  1. 2021f-Domain-Adversarial Learning: Theory and Algorithmscited by 47
  2. 2022Unbalanced Optimal Transport, from Theory to Numericscited by 46
  3. 2021Neural Monge Map estimation and its applicationscited by 40
  4. 2021Sinkhorn Distributionally Robust Optimizationcited by 38
  5. 2022Neural Optimal Transport with General Cost Functionalscited by 36
  6. 2021A Survey on Optimal Transport for Machine Learning: Theory and Applicationscited by 35
  7. 2023Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Modelscited by 33
  8. 2023On the Stability of Expressive Positional Encodings for Graphscited by 33
  9. 2022Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyondcited by 32
  10. 2023The Monge Gap: A Regularizer to Learn All Transport Mapscited by 32
  11. 2023Optimal Transport for Treatment Effect Estimationcited by 32
  12. 2024Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMscited by 32
  13. 2025EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Datacited by 29
  14. 2022Meta Optimal Transportcited by 28
  15. 2023DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matricescited by 28
  16. 2021Transport-based Counterfactual Modelscited by 27
  17. 2023Scalable Optimal Transport Methods in Machine Learning: A Contemporary Surveycited by 27
  18. 2021Conditional Bures Metric for Domain Adaptationcited by 25
  19. 2022Revisiting Sliced Wasserstein on Images: From Vectorization to Convolutioncited by 25
  20. 2022Wasserstein Task Embedding for Measuring Task Similaritiescited by 25
  21. 2022Hierarchical Sliced Wasserstein Distancecited by 23
  22. 2023Quasi-Monte Carlo for 3D Sliced Wassersteincited by 22
  23. 2023Transductive conformal inference with adaptive scorescited by 21
  24. 2022Sliced Optimal Partial Transportcited by 20
  25. 2021Learning Transferable Parameters for Unsupervised Domain Adaptationcited by 19
  26. 2021Mapping conditional distributions for domain adaptation under generalized target shiftcited by 18
  27. 2022Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metricscited by 18
  28. 2023Gradual Domain Adaptation: Theory and Algorithmscited by 18
  29. 2022Improving Transferability for Domain Adaptive Detection Transformerscited by 17
  30. 2023Data Valuation and Detections in Federated Learningcited by 17
  31. 2021Unsupervised Noise Adaptive Speech Enhancement by Discriminator-Constrained Optimal Transportcited by 16
  32. 2023Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Mapscited by 16
  33. 2023Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sourcescited by 16
  34. 2023OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognitioncited by 16
  35. 2021Information-theoretic regularization for Multi-source Domain Adaptationcited by 15
  36. 2024Sinkhorn Distance Minimization for Knowledge Distillationcited by 15
  37. 2022Rethinking Initialization of the Sinkhorn Algorithmcited by 14
  38. 2022Combating Label Distribution Shift for Active Domain Adaptationcited by 14

50 most cited of 282 All 282 (JSON)