Research map / Learning theory and algorithms / Prediction and decision losses
Anisotropic Additive Quantization for Fast Inner Product Search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use anisotropic additive quantization instead of ScaNN | MIPS quantization · LastFM, EchoNest | recall@T | Helped |
| Use anisotropic additive quantization instead of ScaNN | MIPS quantization · Glove1.2M | recall@T | No clear effect |
| Use anisotropic additive quantization instead of SIMPLE-LSH and ip-NSW | MIPS search · LastFM, EchoNest, Glove1.2M | recall@T | Helped |
| Use anisotropic additive quantization instead of ScaNN | MIPS quantization · LastFM | score-aware loss | Helped |
| Use anisotropic additive quantization instead of ScaNN | MIPS quantization · LastFM | relative error of true Top-1 inner-product estimation | Helped |
| Use anisotropic additive quantization instead of ScaNN with the same inverted indexing structure | MIPS search · LastFM | Recall10@100 | Helped |
| Use anisotropic additive quantization instead of ScaNN | MIPS search with inverted indexing · Glove1.2M | search time | No clear effect |
Closest papers by meaning
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- Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search (AAAI 2020 · similarity 0.87)
- Extreme Compression of Large Language Models via Additive Quantization (ICML 2024 · similarity 0.83)
- Faster Maximum Inner Product Search in High Dimensions (ICML 2024 · similarity 0.82)
- Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks (ICLR 2025 · similarity 0.81)
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