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Martin Aumüller
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ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms
M Aumüller, E Bernhardsson, A Faithfull
International Conference on Similarity Search and Applications, 34-49, 2017
2002017
Optimal partitioning for dual-pivot quicksort
M Aumüller, M Dietzfelbinger
ACM Transactions on Algorithms (TALG) 12 (2), 1-36, 2015
462015
Explicit and efficient hash families suffice for cuckoo hashing with a stash
M Aumüller, M Dietzfelbinger, P Woelfel
Algorithmica 70 (3), 428-456, 2014
402014
Parameter-free locality sensitive hashing for spherical range reporting
TD Ahle, M Aumüller, R Pagh
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017
382017
Distance-sensitive hashing
M Aumüller, T Christiani, R Pagh, F Silvestri
Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2018
252018
How good is multi-pivot quicksort?
M Aumüller, M Dietzfelbinger, P Klaue
ACM Transactions on Algorithms (TALG) 13 (1), 1-47, 2016
202016
PUFFINN: parameterless and universally fast finding of nearest neighbors
M Aumüller, T Christiani, R Pagh, M Vesterli
arXiv preprint arXiv:1906.12211, 2019
16*2019
The role of local dimensionality measures in benchmarking nearest neighbor search
M Aumüller, M Ceccarello
Information Systems 101, 101807, 2021
13*2021
Experimental variations of a theoretically good retrieval data structure
M Aumüller, M Dietzfelbinger, M Rink
European Symposium on Algorithms, 742-751, 2009
132009
Sampling a Near Neighbor in High Dimensions--Who is the Fairest of Them All?
M Aumüller, S Har-Peled, S Mahabadi, R Pagh, F Silvestri
arXiv preprint arXiv:2101.10905, 2021
11*2021
Dual-pivot quicksort: Optimality, analysis and zeros of associated lattice paths
M Aumüller, M Dietzfelbinger, C Heuberger, D Krenn, H Prodinger
Combinatorics, Probability and Computing 28 (4), 485-518, 2019
10*2019
Fair near neighbor search via sampling
M Aumuller, S Har-Peled, S Mahabadi, R Pagh, F Silvestri
ACM SIGMOD Record 50 (1), 42-49, 2021
72021
Differentially private sketches for Jaccard similarity estimation
M Aumüller, A Bourgeat, J Schmurr
International Conference on Similarity Search and Applications, 18-32, 2020
52020
A simple hash class with strong randomness properties in graphs and hypergraphs
M Aumüller, M Dietzfelbinger, P Woelfel
arXiv preprint arXiv:1611.00029, 2016
52016
An alternative analysis of cuckoo hashing with a stash and realistic hash functions
M Aumüller
Technische Universität Ilmenau, 2010
52010
On the Analysis of Two Fundamental Randomized Algorithms-Multi-Pivot Quicksort and Efficient Hash Functions
M Aumüller
3*2015
Differentially private sparse vectors with low error, optimal space, and fast access
M Aumüller, CJ Lebeda, R Pagh
Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021
22021
Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme
M Aumüller, N Hass
2019 Proceedings of the Twenty-First Workshop on Algorithm Engineering and …, 2019
22019
DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search
M Karppa, M Aumüller, R Pagh
International Conference on Artificial Intelligence and Statistics, 3108-3137, 2022
12022
Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search
H Vardhan Simhadri, G Williams, M Aumüller, M Douze, A Babenko, ...
arXiv e-prints, arXiv: 2205.03763, 2022
1*2022
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