Unverified Commit b95027ad authored by Matthijs Douze's avatar Matthijs Douze Committed by GitHub

Update README.md

parent a8199f06
......@@ -10,12 +10,14 @@ Link & code is an indexing method that combines HNSW indexing with
compression and exploits the neighborhood structure of the similarity
graph to improve the reconstruction. It is described in
```
@inproceedings{link_and_code,
author = {Matthijs Douze and Alexandre Sablayrolles and Herv\'e J\'egou},
title = {Link and code: Fast indexing with graphs and compact regression codes},
booktitle = {CVPR},
year = {2018}
}
```
ArXiV [here](https://arxiv.org/abs/1804.09996)
......@@ -28,7 +30,7 @@ The test runs with 3 files:
- `datasets.py`: code to load the datasets. The example code runs on the
deep1b and bigann datasets. See the [toplevel README](../README.md)
on how to downlod them. They should be put in a directory, edit
on how to download them. They should be put in a directory, edit
datasets.py to set the path.
- `neighbor_codec.py`: this is where the representation is trained.
......@@ -60,7 +62,7 @@ Set `bdir` to a scratch directory.
Explanation of the flags:
- `--db deep1M`: dataset to process
- `--db deep100M`: dataset to process
- `--M0 6`: number of links on the base level (L6)
......
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