Research map / Learning theory and algorithms / Prediction and decision losses
An algorithm for L1 nearest neighbor search via monotonic embedding
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace Cauchy random projection LSH with ERP (l1 to l2^2 embedding + Gaussian projection) LSH | LSH for l1 NN search · Corel uci, Corel hist, Cade, ImageNet | average query cost | Mixed |
| ERP-LSH vs Cauchy LSH (CRP-LSH) | Cade dataset (d=120) · Cade | average query cost: 218 vs 292 | Helped |
| ERP-LSH vs Cauchy LSH (CRP-LSH) | ImageNet dataset (d=100) · ImageNet | average query cost: 346 vs 548 | Helped |
| ERP-LSH vs metric tree for exact search | LSH-based l1 NN search · Corel uci, Corel hist, Cade, ImageNet | average query cost: ERP-LSH well below metric tree on Cade (218 vs 9184) and ImageNet (346 vs 12375); metric tree is better on Corel uci (25 | Helped |
| Gaussian random projection of l1-embedded data (ERP) vs linear scan | LSH for l1 NN search · all four datasets | average query cost: e.g. 218 vs 11715 on Cade | Helped |
Closest papers by meaning
- Improved nearest neighbor search using auxiliary information and priority functions (ICML 2018 · similarity 0.89)
- Graph-based Nearest Neighbor Search: From Practice to Theory (ICML 2020 · similarity 0.89)
- Graph-Based Algorithms for Diverse Similarity Search (ICML 2025 · similarity 0.88)
- Discovering Data Structures: Nearest Neighbor Search and Beyond (NeurIPS 2025 · similarity 0.88)
- Weighted distance nearest neighbor condensing (ICML 2024 · similarity 0.87)
- Approximate Nearest Neighbor Search with Window Filters (ICML 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.