An important by-product of Leonid's research is an efficient and flexible library for k-NN search codenamed NMSLIB created in collaboration with several other folks. Thanks to the contribution of Yury Malkov, the library was adopted by Amazon . The core retrieval method HNSW contributed by Yury was also reimplemented in the Facebook library FAISS . A brief description of this collaboration can be found on this LTI news page . This work is discussed in a podcast with Radim Řehůřek (author of Gensim) in March
NMSLIB integrates with another retrieval toolkit called FlexNeuART , which in August, November and December 2020 produced best neural and traditional submissions on the MS MARCO document ranking leaderboard. In that, the strongest traditional run outperformed a number of neural systems.
Leonid also co-authored an extremely efficient algorithm for light-weight compression of sorted integer numbers. We show that this algorithm can decompress at the speed of reading from memory. You can find software on GitHub. This software grew out of a now-popular library FastPFor. FastPFor has Python bindings.