Accelerating Large-Scale Inference with Anisotropic Vector Quantization

ICLR 2020 Ruiqi GuoPhilip SunErik LindgrenQuan GengDavid SimchaFelix ChernSanjiv Kumar

Quantization based techniques are the current state-of-the-art for scaling maximum inner product search to massive databases. Traditional approaches to quantization aim to minimize the reconstruction error of the database points... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet