Results of the Big ANN: NeurIPS'23 competition.
- Harsha Vardhan Simhadri,
- ,
- Amir Ingber,
- Matthijs Douze,
- George Williams,
- Magdalen Dobson Manohar
- Microsoft,
- ,
- Pinecone,
- Meta AI,
- Carnegie Mellon University,
- Yandex
Research Output:
Journal Article or Conference Article in Journal
Journal article
Open access
Publication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Original language
EnglishJournal (Volume, Issue Number)
CoRR (Volume abs/2409.17424)Publication milestones
- Published - 2024
Publication status
Published - 2024
ISSN
0000-0000Abstract
The 2023 Big ANN Challenge, held at NeurIPS 2023, focused on advancing the state-of-the-art in indexing data structures and search algorithms for practical variants of Approximate Nearest Neighbor (ANN) search that reflect the growing complexity and diversity of workloads. Unlike prior challenges that emphasized scaling up classical ANN search [21], this competition addressed filtered search, out-of-distribution data, sparse and streaming variants of ANNS. Participants developed and submitted innovative solutions that were evaluated on new standard datasets with constrained computational resources. The results showcased significant improvements in search accuracy and efficiency over industry-standard baselines, with notable contributions from both academic and industrial teams. This paper summarizes the competition tracks, datasets, evaluation metrics, and the innovative approaches of the top-performing submissions, providing insights into the current advancements and future directions in the field of approximate nearest neighbor search.
