ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms

Bentley, J.L.: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509–517 (1975)

1975

Earlier work this paper cites.

Johnson, W.B., Lindenstrauss, J., Schechtman, G.: Extensions of lipschitz maps into banach spaces. Israel Journal of Mathematics 54(2), 129–138 (1986)

1986

Earlier work this paper cites.

Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: VLDB’97. pp. 426–435 (1997)

1997

Earlier work this paper cites.

LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proceedings of the IEEE 86(11), 2278–2324 (1998)

1998

Earlier work this paper cites.

Zezula, P., Savino, P., Amato, G., Rabitti, F.: Approximate similarity retrieval with M-Trees. VLDB J. 7(4), 275–293 (1998)

Original

1998

Earlier work this paper cites.

Williams, R.: A new algorithm for optimal 2-constraint satisfaction and its implications. Theor. Comput. Sci. 348(2-3), 357–365 (2005)

2005

Earlier work this paper cites.

Curtin, R.R., Cline, J.R., Slagle, N.P., March, W.B., Ram, P., Mehta, N.A., Gray, A.G.: MLPACK: A scalable C++ machine learning library. Journal of Machine Learning Research 14, 801–805 (2013)

2013

Earlier work this paper cites.

Van Rijn, J.N., Bischl, B., Torgo, L., Gao, B., Umaashankar, V., Fischer, S., Winter, P., Wiswedel, B., Berthold, M.R., Vanschoren, J.: Openml: A collaborative science platform. In: ECML PKDD. pp. 645–649. Springer (2013)

2013

Earlier work this paper cites.

Edel, M., Soni, A., Curtin, R.R.: An automatic benchmarking system. In: NIPS 2014 Workshop on Software Engineering for Machine Learning (2014)

2014

Cited alongside, same era.

Malkov, Y., Ponomarenko, A., Logvinov, A., Krylov, V.: Approximate nearest neighbor algorithm based on navigable small world graphs. Inf. Syst. 45, 61–68 (2014)

2014

Cited alongside, same era.

Wang, J., Shen, H.T., Song, J., Ji, J.: Hashing for similarity search: A survey. CoRR abs/1408.2927 (2014), http://arxiv.org/abs/1408.2927

Original

2014

Cited alongside, same era.

Heo, J.P., Lee, Y., He, J., Chang, S.F., Yoon, S.E.: Spherical hashing: Binary code embedding with hyperspheres. IEEE TPAMI 37(11), 2304–2316 (2015)

2015

Cited alongside, same era.

Malkov, Y.A., Yashunin, D.A.: Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs. ArXiv e-prints (Mar 2016)

2016

Later among the works it cites.

Johnson, J., Douze, M., Jégou, H.: Billion-scale similarity search with gpus. CoRR abs/1702.08734 (2017)

Original

2017

Later among the works it cites.

Kriegel, H., Schubert, E., Zimek, A.: The (black) art of runtime evaluation: Are we comparing algorithms or implementations? Knowl. Inf. Syst. 52(2), 341–378 (2017)

2017

Later among the works it cites.

Christiani, T., Pagh, R., Sivertsen, J.: Scalable and robust set similarity join. In: ICDE’2018 (2018)

2018

Closest in time.