Research map / Learning theory and algorithms / Combinatorial and search optimization
Simple and Efficient Weighted Minwise Hashing
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| rejection-sampling weighted minwise hashing (red-green map) replacing Ioffe's CWS | weighted minwise hashing · Oxford, Caltech101, Hist (500 hashes) | time to compute 500 hashes: up to ~60000x faster than Ioffe on Oxford/Caltech101 | Helped |
| rejection-sampling WMH replacing Fast-WDOPH biased approximation | weighted minwise hashing · Caltech101, Oxford, Hist | time to compute 500 hashes: roughly 5 to 100x faster | Helped |
| rejection-sampling WMH (proposed) vs Ioffe's exact CWS | weighted minwise hashing · Sim=0.8 to 0.27 pairs, k=1..50 | Jaccard estimation error | No clear effect |
| replace weighted-to-unweighted reduction (Fast-WDOPH) with exact unbiased sampling | weighted minwise hashing · Jaccard estimation, 9 vector pairs | estimation error | Helped |
| rejection sampling hash bit width instead of 32-64 bit hashes | weighted minwise hashing · Hist, Caltech101, Oxford | bits needed per hash: 7-9 bits vs 32-64 bits | Helped |
Closest papers by meaning
- Re-randomized Densification for One Permutation Hashing and Bin-wise Consistent Weighted Sampling (NeurIPS 2019 · similarity 0.90)
- C-MinHash: Improving Minwise Hashing with Circulant Permutation (ICML 2022 · similarity 0.89)
- Optimal Densification for Fast and Accurate Minwise Hashing (ICML 2017 · similarity 0.89)
- Practical Hash Functions for Similarity Estimation and Dimensionality Reduction (NeurIPS 2017 · similarity 0.86)
- Sublinear Time Nearest Neighbor Search over Generalized Weighted Space (ICML 2019 · similarity 0.85)
- Dual Self-Paced Cross-Modal Hashing (AAAI 2024 · similarity 0.83)
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