CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors

Author:

Mic VladimirORCID,Sedmidubsky JanORCID,Zezula PavelORCID

Publisher

Springer Nature Switzerland

Reference10 articles.

1. Amsaleg, L., et al.: Estimating local intrinsic dimensionality. In: Proceedings of the International Conference on Knowledge Discovery and Data Mining, pp. 29–38. KDD 2015, ACM, USA (2015)

2. Mic, V.: Binary Sketches for Similarity Search. Dissertation thesis, Masaryk University Brno (2020). https://theses.cz/id/c7kstr/. supervisor: Pavel Zezula

3. Mic, V., Novak, D., Zezula, P.: Improving sketches for similarity search. In: Tenth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science (MEMICS 2015), pp. 45–57 (2015)

4. Mic, V., Novak, D., Zezula, P.: Designing sketches for similarity filtering. In: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp. 655–662 (2016)

5. Mic, V., Novak, D., Zezula, P.: Binary sketches for secondary filtering. ACM Trans. Inf. Syst. 37(1), 1:1–1:28 (2018)

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1. Overview of the SISAP 2023 Indexing Challenge;Similarity Search and Applications;2023

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