Martin Aumüller

According to our database, Martin Aumüller authored at least 42 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

PLAN: Variance-Aware Private Mean Estimation.

Martin Aumüller, Christian Janos Lebeda, Boel Nelson, Rasmus Pagh

Proc. Priv. Enhancing Technol., 2024

Results of the Big ANN: NeurIPS'23 competition.

Harsha Vardhan Simhadri, Martin Aumüller, Amir Ingber, Matthijs Douze, George Williams, Magdalen Dobson Manohar, Dmitry Baranchuk, Edo Liberty, Frank Liu, Benjamin Landrum, Mazin Karjikar, Laxman Dhulipala, Meng Chen, Yue Chen, Rui Ma, Kai Zhang, Yuzheng Cai, Jiayang Shi, Yizhuo Chen, Weiguo Zheng, Zihao Wan, Jie Yin, Ben Huang

CoRR, 2024

A Simple Linear Space Data Structure for ANN with Application in Differential Privacy.

Martin Aumüller, Fabrizio Boninsegna, Francesco Silvestri

CoRR, 2024

Overview of the SISAP 2024 Indexing Challenge.

Eric Sadit Tellez, Martin Aumüller, Vladimir Mic

Proceedings of the Similarity Search and Applications - 17th International Conference, 2024

On the Design of Scalable Outlier Detection Methods Using Approximate Nearest Neighbor Graphs.

Camilla Birch Okkels, Martin Aumüller, Arthur Zimek

Proceedings of the Similarity Search and Applications - 17th International Conference, 2024

An Empirical Evaluation of Search Strategies for Locality-Sensitive Hashing: Lookup, Voting, and Natural Classifier Search.

Malte Helin Johnsen, Martin Aumüller

Proceedings of the Similarity Search and Applications - 17th International Conference, 2024

2023

Recent Approaches and Trends in Approximate Nearest Neighbor Search, with Remarks on Benchmarking.

Martin Aumüller, Matteo Ceccarello

IEEE Data Eng. Bull., 2023

Overview of the SISAP 2023 Indexing Challenge.

Eric Sadit Tellez, Martin Aumüller, Edgar Chávez

Proceedings of the Similarity Search and Applications - 16th International Conference, 2023

Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback.

Omar Shahbaz Khan, Martin Aumüller, Björn Þór Jónsson

Proceedings of the Similarity Search and Applications - 16th International Conference, 2023

Solving k-Closest Pairs in High-Dimensional Data.

Martin Aumüller, Matteo Ceccarello

Proceedings of the Similarity Search and Applications - 16th International Conference, 2023

2022

Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All?

Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

ACM Trans. Database Syst., 2022

Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access.

Christian Janos Lebeda, Martin Aumüller, Rasmus Pagh

J. Priv. Confidentiality, 2022

Sampling near neighbors in search for fairness.

Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

Commun. ACM, 2022

Implementing Distributed Similarity Joins using Locality Sensitive Hashing.

Martin Aumüller, Matteo Ceccarello

Proceedings of the 25th International Conference on Extending Database Technology, 2022

DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search.

Matti Karppa, Martin Aumüller, Rasmus Pagh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Fair near neighbor search via sampling.

Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

SIGMOD Rec., 2021

The role of local dimensionality measures in benchmarking nearest neighbor search.

Martin Aumüller, Matteo Ceccarello

Inf. Syst., 2021

Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search.

Harsha Vardhan Simhadri, George Williams, Martin Aumüller, Matthijs Douze, Artem Babenko, Dmitry Baranchuk, Qi Chen, Lucas Hosseini, Ravishankar Krishnaswamy, Gopal Srinivasa, Suhas Jayaram Subramanya, Jingdong Wang

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Differentially Private Sparse Vectors with Low Error, Optimal Space, and Fast Access.

Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020

ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms.

Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull

Inf. Syst., 2020

Algorithm Engineering for High-Dimensional Similarity Search Problems (Invited Talk).

Martin Aumüller

Proceedings of the 18th International Symposium on Experimental Algorithms, 2020

Running Experiments with Confidence and Sanity.

Martin Aumüller, Matteo Ceccarello

Proceedings of the Similarity Search and Applications - 13th International Conference, 2020

Differentially Private Sketches for Jaccard Similarity Estimation.

Martin Aumüller, Anders Bourgeat, Jana Schmurr

Proceedings of the Similarity Search and Applications - 13th International Conference, 2020

Fair Near Neighbor Search: Independent Range Sampling in High Dimensions.

Martin Aumüller, Rasmus Pagh, Francesco Silvestri

Proceedings of the 39th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2020

Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN.

Quoc-Tuan Truong, Hady W. Lauw, Martin Aumüller, Naoko Nitta

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

2019

Dual-Pivot Quicksort: Optimality, Analysis and Zeros of Associated Lattice Paths.

Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger

Comb. Probab. Comput., 2019

The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search.

Martin Aumüller, Matteo Ceccarello

Proceedings of the Similarity Search and Applications - 12th International Conference, 2019

Benchmarking Nearest Neighbor Search: Influence of Local Intrinsic Dimensionality and Result Diversity in Real-World Datasets.

Martin Aumüller, Matteo Ceccarello

Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), 2019

PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors.

Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli

Proceedings of the 27th Annual European Symposium on Algorithms, 2019

Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme.

Martin Aumüller, Nikolaj Hass

Proceedings of the Twenty-First Workshop on Algorithm Engineering and Experiments, 2019

2018

Distance-Sensitive Hashing.

Martin Aumüller, Tobias Christiani, Rasmus Pagh, Francesco Silvestri

Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2018

2017

Theory and Applications of Hashing (Dagstuhl Seminar 17181).

Martin Dietzfelbinger, Michael Mitzenmacher, Rasmus Pagh, David P. Woodruff, Martin Aumüller

Dagstuhl Reports, 2017

Parameter-free Locality Sensitive Hashing for Spherical Range Reporting.

Thomas D. Ahle, Martin Aumüller, Rasmus Pagh

Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

2016

How Good Is Multi-Pivot Quicksort?

Martin Aumüller, Martin Dietzfelbinger, Pascal Klaue

ACM Trans. Algorithms, 2016

Optimal Partitioning for Dual-Pivot Quicksort.

Martin Aumüller, Martin Dietzfelbinger

ACM Trans. Algorithms, 2016

A Simple Hash Class with Strong Randomness Properties in Graphs and Hypergraphs.

Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel

CoRR, 2016

Counting Zeros in Random Walks on the Integers and Analysis of Optimal Dual-Pivot Quicksort.

Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger

CoRR, 2016

High-dimensional Spherical Range Reporting by Output-Sensitive Multi-Probing LSH.

Thomas D. Ahle, Martin Aumüller, Rasmus Pagh

CoRR, 2016

2015

On the Analysis of Two Fundamental Randomized Algorithms - Multi-Pivot Quicksort and Efficient Hash Functions.

Martin Aumüller

PhD thesis, 2015

2014

Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash.

Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel

Algorithmica, 2014

2013

Optimal Partitioning for Dual Pivot Quicksort - (Extended Abstract).

Martin Aumüller, Martin Dietzfelbinger

Proceedings of the Automata, Languages, and Programming - 40th International Colloquium, 2013

2009

Experimental Variations of a Theoretically Good Retrieval Data Structure.

Martin Aumüller, Martin Dietzfelbinger, Michael Rink

Proceedings of the Algorithms, 2009