Research map / Learning theory and algorithms / Optimal transport
Optimal Tensor Transport
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use OTT to align the full user-movie comparison tensor rather than matrix-reduced baselines | Movielens DA · Movielens DA: AVG | accuracy: 68.2 -> 77.3±3 | Helped |
| Use OTT instead of Co-OT | Movielens DA · Movielens DA: F,C | accuracy: 74.0 -> 70.2±4 | Hurt |
| Tune hyperparameters using the source-target distance | Movielens DA methods · Movielens DA | accuracy | Helped |
| Increase the number of labeled target examples | OTT and DA baselines · Movielens DA | accuracy | Helped |
| Provide more known user correspondences across old and new movies | OTT and methods that handle user matching · Movielens DA | accuracy | Helped |
| Replace k-means with an OT barycenter step that uses cluster proportions (ablation) | AddS3 comparison-based clustering · MNIST comparison-based clustering: AVG | ARI: 34±9 -> 81±16 | Helped |
| Replace k-means with an OT barycenter step that uses cluster proportions (ablation) | t-STE comparison-based clustering · MNIST comparison-based clustering: AVG | ARI: 51±10 -> 91±8 | Helped |
| Use OTT rather than t-STE with the OT barycenter step | MNIST comparison-based clustering · MNIST comparison-based clustering: AVG | ARI: 91±8 -> 89±10 | Hurt |
Closest papers by meaning
- CO-Optimal Transport (NeurIPS 2020 · similarity 0.91)
- A Swiss Army Knife for Minimax Optimal Transport (ICML 2020 · similarity 0.89)
- Hierarchical Refinement: Optimal Transport to Infinity and Beyond (ICML 2025 · similarity 0.89)
- Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling (NeurIPS 2024 · similarity 0.89)
- Geometry-Aware Optimal Transport: Fast Intrinsic Dimension and Wasserstein Distance Estimation (NeurIPS 2026 · similarity 0.88)
- Double-Bounded Optimal Transport for Advanced Clustering and Classification (AAAI 2024 · similarity 0.87)
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