Martin Aumüller

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 47

Top Venues

Technische Universität Ilmenau, Germany (PHD)

Education History

Technische Universität Ilmenau, Germany

PHD

Publications

Martin Aumüller, Christian Janos Lebeda, Boel Nelson, Rasmus Pagh
PLAN: Variance-Aware Private Mean Estimation. Proc. Priv. Enhancing Technol. 2024 (3) (2024)
Omar Shahbaz Khan, Martin Aumüller, Björn Þór Jónsson
Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback. SISAP (2023)
Martin Aumüller, Christian Janos Lebeda, Boel Nelson, Rasmus Pagh
PLAN: Variance-Aware Private Mean Estimation. CoRR (2023)
Martin Aumüller, Matteo Ceccarello
Recent Approaches and Trends in Approximate Nearest Neighbor Search, with Remarks on Benchmarking. IEEE Data Eng. Bull. 46 (3) (2023)
Martin Aumüller, Matteo Ceccarello
Solving k-Closest Pairs in High-Dimensional Data. SISAP (2023)
Eric Sadit Tellez, Martin Aumüller, Edgar Chávez
Overview of the SISAP 2023 Indexing Challenge. SISAP (2023)
Matti Karppa, Martin Aumüller, Rasmus Pagh
DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search. AISTATS (2022)
Christian Janos Lebeda, Martin Aumüller, Rasmus Pagh
Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access. J. Priv. Confidentiality 12 (2) (2022)
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All? ACM Trans. Database Syst. 47 (1) (2022)
Martin Aumüller, Matteo Ceccarello
Implementing Distributed Similarity Joins using Locality Sensitive Hashing. EDBT (2022)
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
Sampling near neighbors in search for fairness. Commun. ACM 65 (8) (2022)
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
Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. CoRR (2022)
Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh
Differentially private sparse vectors with low error, optimal space, and fast access. CoRR (2021)
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All? CoRR (2021)
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
Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. NeurIPS (Competition and Demos) (2021)
Matti Karppa, Martin Aumüller, Rasmus Pagh
DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search. CoRR (2021)
Martin Aumüller, Matteo Ceccarello
The role of local dimensionality measures in benchmarking nearest neighbor search. Inf. Syst. 101 (2021)
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
Fair near neighbor search via sampling. SIGMOD Rec. 50 (1) (2021)
Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh
Differentially Private Sparse Vectors with Low Error, Optimal Space, and Fast Access. CCS (2021)
Martin Aumüller, Rasmus Pagh, Francesco Silvestri
Fair Near Neighbor Search: Independent Range Sampling in High Dimensions. PODS (2020)
Quoc-Tuan Truong, Hady W. Lauw, Martin Aumüller, Naoko Nitta
Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN. ACM Multimedia (2020)
Martin Aumüller, Anders Bourgeat, Jana Schmurr
Differentially Private Sketches for Jaccard Similarity Estimation. SISAP (2020)
Martin Aumüller
Algorithm Engineering for High-Dimensional Similarity Search Problems (Invited Talk). SEA (2020)
Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms. Inf. Syst. 87 (2020)
Martin Aumüller, Anders Bourgeat, Jana Schmurr
Differentially Private Sketches for Jaccard Similarity Estimation. CoRR (2020)
Martin Aumüller, Matteo Ceccarello
Running Experiments with Confidence and Sanity. SISAP (2020)
Martin Aumüller, Nikolaj Hass
Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme. ALENEX (2019)
Martin Aumüller, Rasmus Pagh, Francesco Silvestri
Fair Near Neighbor Search: Independent Range Sampling in High Dimensions. CoRR (2019)
Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
Dual-Pivot Quicksort: Optimality, Analysis and Zeros of Associated Lattice Paths. Comb. Probab. Comput. 28 (4) (2019)
Martin Aumüller, Matteo Ceccarello
Benchmarking Nearest Neighbor Search: Influence of Local Intrinsic Dimensionality and Result Diversity in Real-World Datasets. EDML@SDM (2019)
Martin Aumüller, Matteo Ceccarello
The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search. SISAP (2019)
Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli
PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors. CoRR (2019)
Martin Aumüller, Matteo Ceccarello
The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search. CoRR (2019)
Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli
PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors. ESA (2019)
Martin Aumüller, Nikolaj Hass
Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme. CoRR (2018)
Martin Aumüller, Tobias Christiani, Rasmus Pagh, Francesco Silvestri
Distance-Sensitive Hashing. PODS (2018)
Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms. CoRR (2018)
Thomas D. Ahle, Martin Aumüller, Rasmus Pagh
Parameter-free Locality Sensitive Hashing for Spherical Range Reporting. SODA (2017)
Martin Dietzfelbinger, Michael Mitzenmacher, Rasmus Pagh, David P. Woodruff, Martin Aumüller
Theory and Applications of Hashing (Dagstuhl Seminar 17181). Dagstuhl Reports 7 (5) (2017)
Martin Aumüller, Tobias Christiani, Rasmus Pagh, Francesco Silvestri
Distance-sensitive hashing. CoRR (2017)
Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms. SISAP (2017)
Martin Aumüller, Martin Dietzfelbinger
Optimal Partitioning for Dual-Pivot Quicksort. ACM Trans. Algorithms 12 (2) (2016)
Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
A Simple Hash Class with Strong Randomness Properties in Graphs and Hypergraphs. CoRR (2016)
Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
Dual-Pivot Quicksort: Optimality, Analysis and Zeros of Associated Lattice Paths. CoRR (2016)
Martin Aumüller, Martin Dietzfelbinger, Pascal Klaue
How Good Is Multi-Pivot Quicksort? ACM Trans. Algorithms 13 (1) (2016)
Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
Counting Zeros in Random Walks on the Integers and Analysis of Optimal Dual-Pivot Quicksort. CoRR (2016)
Thomas D. Ahle, Martin Aumüller, Rasmus Pagh
High-dimensional Spherical Range Reporting by Output-Sensitive Multi-Probing LSH. CoRR (2016)
Martin Aumüller, Martin Dietzfelbinger, Pascal Klaue
How Good is Multi-Pivot Quicksort? CoRR (2015)
Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash. Algorithmica 70 (3) (2014)
Martin Aumüller, Martin Dietzfelbinger
Optimal Partitioning for Dual Pivot Quicksort CoRR (2013)
Martin Aumüller, Martin Dietzfelbinger
Optimal Partitioning for Dual Pivot Quicksort - (Extended Abstract). ICALP (1) (2013)
Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash. ESA (2012)
Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash CoRR (2012)
Martin Aumüller, Martin Dietzfelbinger, Michael Rink
Experimental Variations of a Theoretically Good Retrieval Data Structure. ESA (2009)

Martin Aumüller.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Martin Aumüller