Research map / Label-efficient and robust learning / Recognition and long-tail
A Multilabel Classification Framework for Approximate Nearest Neighbor Search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace lookup-based candidate selection with the natural classifier | Ensembles of randomized k-d, RP, and PCA trees · Trevi and the other tested datasets | query time at a given recall | Helped |
| Use a supervised random forest rather than an unsupervised tree | Tree-based ANN search · Fashion and GIST | query time at a given recall: Fashion: 0.075 -> 0.063; GIST: 0.958 -> 0.705 | Helped |
| Use a supervised random forest rather than a PCA tree | Tree-based ANN search · STL-10 and Trevi | query time at a given recall: STL-10: 0.382 -> 0.756; Trevi: 0.330 -> 0.582 | Hurt |
Closest papers by meaning
- Approximate Nearest Neighbor Search with Window Filters (ICML 2024 · similarity 0.87)
- LotusFilter: Fast Diverse Nearest Neighbor Search via a Learned Cutoff Table (CVPR 2025 · similarity 0.85)
- LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search (NeurIPS 2024 · similarity 0.85)
- Discovering Data Structures: Nearest Neighbor Search and Beyond (NeurIPS 2025 · similarity 0.85)
- Graph-Based Algorithms for Diverse Similarity Search (ICML 2025 · similarity 0.85)
- Weighted distance nearest neighbor condensing (ICML 2024 · similarity 0.84)
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