Fetching the paper…
Reading the bibliography…
Graph-based approaches are empirically shown to be very successful for the nearest neighbor search (NNS).
Multidimensional binary search trees used for associative searching
Bentley, J. L · 1975
Earlier work this paper cites.
The diameter of a cycle plus a random matching
B. Bollobás and F. R. K. Chung · 1988
Earlier work this paper cites.
Point location in arrangements of hyperplanes
Meiser, S · 1993
Earlier work this paper cites.
The smallest uniform upper bound on the distance between the mean and the median of the binomial and poisson distributions
K. Hamza · 1995
Earlier work this paper cites.
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Arya, S., Mount, D. M., Netanyahu, N. S., Silverman, R., and Wu, A. Y · 1998
Earlier work this paper cites.
Approximate nearest neighbors: towards removing the curse of dimensionality
Indyk, P. and Motwani, R · 1998
Earlier work this paper cites.
Collective dynamics of ‘small-world’networks
Watts, D. J. and Strogatz, S. H · 1998
Earlier work this paper cites.
Collective dynamics of ‘small-world’networks
D. J. Watts and S. H. Strogatz · 1998
Earlier work this paper cites.
On k-connectivity for a geometric random graph
M. D. Penrose · 1999
Earlier work this paper cites.
The small-world phenomenon: an algorithmic perspective
Kleinberg, J · 2000
Earlier work this paper cites.
Efficient routing in networks with long range contacts
Barrière, L., Fraigniaud, P., Kranakis, E., and Krizanc, D · 2001
Earlier work this paper cites.
Searching in metric spaces by spatial approximation
Navarro, G · 2002
Earlier work this paper cites.
Locality-sensitive hashing scheme based on p-stable distributions
Datar, M., Immorlica, N., Indyk, P., and Mirrokni, V. S · 2004
Earlier work this paper cites.
Maximum likelihood estimation of intrinsic dimension
E. Levina and P. J. Bickel · 2005
Earlier work this paper cites.
Cover trees for nearest neighbor
Beygelzimer, A., Kakade, S., and Langford, J · 2006
Earlier work this paper cites.
Pattern recognition and machine learning
Bishop, C. M · 2006
Earlier work this paper cites.
Could any graph be turned into a small-world?
Duchon, P., Hanusse, N., Lebhar, E., and Schabanel, N · 2006
Earlier work this paper cites.
Nearest-neighbor methods in learning and vision: theory and practice (neural information processing)
Shakhnarovich, G., Darrell, T., and Indyk, P · 2006
Earlier work this paper cites.
Peer to peer multidimensional overlays: approximating complex structures
Beaumont, O., Kermarrec, A.-M., and Rivière, É · 2007
Earlier work this paper cites.
Small-world networks: is there a mismatch between theory and practice?
Bonnet, F., Kermarrec, A.-M., and Raynal, M · 2007
Cited alongside, same era.
Lower bounds on locality sensitive hashing
Motwani, R., Naor, A., and Panigrahy, R · 2007
Cited alongside, same era.
Near-optimal hashing algorithms for near neighbor problem in high dimension
Andoni, A. and Indyk, P · 2008
Cited alongside, same era.
Random projection trees and low dimensional manifolds
Dasgupta, S. and Freund, Y · 2008
Cited alongside, same era.
Top 10 algorithms in data mining
Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Philip, S. Y., et al · 2008
Cited alongside, same era.
Product quantization for nearest neighbor search
Jegou, H., Douze, M., and Schmid, C · 2010
Cited alongside, same era.
Tight lower bounds for data-dependent locality-sensitive hashing
Andoni, A. and Razensteyn, I · 2016
Later among the works it cites.
Efficient indexing of billion-scale datasets of deep descriptors
Babenko, A. and Lempitsky, V · 2016
Later among the works it cites.
New directions in nearest neighbor searching with applications to lattice sieving
Becker, A., Ducas, L., Gama, N., and Laarhoven, T · 2016
Later among the works it cites.
Fanng: Fast approximate nearest neighbour graphs
Harwood, B. and Drummond, T · 2016
Later among the works it cites.
New directions in nearest neighbor searching with applications to lattice sieving
A. Becker, L. Ducas, N. Gama, and T. Laarhoven · 2016
Later among the works it cites.
Connectivity of soft random geometric graphs
M. D. Penrose et al · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Efficient k-nearest neighbor graph construction for generic similarity measures
Dong, W., Moses, C., and Li, K · 2011
Cited alongside, same era.
Fast approximate nearest-neighbor search with k-nearest neighbor graph
Hajebi, K., Abbasi-Yadkori, Y., Shahbazi, H., and Zhang, H · 2011
Cited alongside, same era.
Approximate nearest neighbor: Towards removing the curse of dimensionality
Har-Peled, S., Indyk, P., and Motwani, R · 2012
Cited alongside, same era.
Scalable k k -NN graph construction for visual descriptors
Wang, J., Wang, J., Zeng, G., Tu, Z., Gan, R., and Li, S · 2012
Cited alongside, same era.
Approximate nearest neighbor algorithm based on navigable small world graphs
Malkov, Y., Ponomarenko, A., Logvinov, A., and Krylov, V · 2014
Cited alongside, same era.
Optimal lower bounds for locality-sensitive hashing (except when q is tiny)
O’Donnell, R., Wu, Y., and Zhou, Y · 2014
Cited alongside, same era.
Optimal hashing-based time-space trade-offs for approximate near neighbors
Andoni, A., Laarhoven, T., Razenshteyn, I., and Waingarten, E · 2017
Later among the works it cites.
Explaining the success of nearest neighbor methods in prediction
Chen, G. H. and Shah, D · 2018
Later among the works it cites.
Iwasaki, M. and Miyazaki, D · 2018
Later among the works it cites.
Improved nearest neighbor search using auxiliary information and priority functions
Keivani, O. and Sinha, K · 2018
Later among the works it cites.
Graph-based time-space trade-offs for approximate near neighbors
Laarhoven, T · 2018
Later among the works it cites.
Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs
Malkov, Y. A. and Yashunin, D. A · 2018
Later among the works it cites.
Spreading vectors for similarity search
Sablayrolles, A., Douze, M., Schmid, C., and Jégou, H · 2018
Later among the works it cites.
Graph-based time-space trade-offs for approximate near neighbors
T. Laarhoven · 2018
Later among the works it cites.
ANN-benchmarks: a benchmarking tool for approximate nearest neighbor algorithms
Aumüller, M., Bernhardsson, E., and Faithfull, A · 2019
Closest in time.
Learning to route in similarity graphs
Baranchuk, D., Persiyanov, D., Sinitsin, A., and Babenko, A · 2019
Closest in time.
Fast approximate nearest neighbor search with the navigating spreading-out graph
Fu, C., Xiang, C., Wang, C., and Cai, D · 2019
Closest in time.
Graph based nearest neighbor search: promises and failures
Lin, P.-C. and Zhao, W.-L · 2019
Closest in time.