This competition focuses on developing indexing data structures and search algorithms for practical settings of the Approximate Nearest Neighbor (ANN) or Vector search problem. The challenge has four tracks covering sparse, filtered, out-of-distribution and streaming variants of ANNs. These variants require adapted search algorithms and strategies with different tradeoffs. 

More details are on the [competition’s website](https://big-ann-benchmarks.com/neurips23.html). 

We encourage everyone to join by August 30th, 2023!

Nearest neighbor search is a long-standing problem arising in a large number of machine learning applications, such as recommender services, information retrieval, and others.

Nearest neighbor search

This competition focuses on developing indexing data structures and search algorithms for practical settings of the Approximate Nearest Neighbor (ANN) or Vector search problem. More details are on the competition’s website. We encourage everyone to join by August 30th, 2023!


NeurIPS 2023 Competition Track: Big-ANN