Martin Aumüller

67 papers A* 5A 5B 16Journal 36Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functions. CoRR Atsuki Sato, Martin Aumüller, Yusuke Matsui
2025	B	`conf`	Approximate Single-Linkage Clustering Using Graph-Based Indexes: MST-Based Approaches and Incremental Searchers. SISAP Camilla Birch Okkels, Erik Thordsen, Martin Aumüller, Arthur Zimek, Erich Schubert
2025	—	`conf`	Differentially Private High-Dimensional Approximate Range Counting, Revisited. FORC Martin Aumüller, Fabrizio Boninsegna, Francesco Silvestri
2025	B	`conf`	High-dimensional density-based clustering using locality-sensitive hashing. EDBT Camilla Birch Okkels, Martin Aumüller, Viktor Bello Thomsen, Arthur Zimek
2025	B	`conf`	Overview of the SISAP 2025 Indexing Challenge. SISAP Eric Sadit Tellez, Edgar Chávez, Martin Aumüller, Vladimir Mic
2025	J	`jnl`	VIBE: Vector Index Benchmark for Embeddings. CoRR Elias Jääsaari, Ville Hyvönen, Matteo Ceccarello, Teemu Roos, Martin Aumüller
2024	J	`jnl`	A Simple Linear Space Data Structure for ANN with Application in Differential Privacy. CoRR Martin Aumüller, Fabrizio Boninsegna, Francesco Silvestri
2024	B	`conf`	An Empirical Evaluation of Search Strategies for Locality-Sensitive Hashing: Lookup, Voting, and Natural Classifier Search. SISAP Malte Helin Johnsen, Martin Aumüller
2024	B	`conf`	On the Design of Scalable Outlier Detection Methods Using Approximate Nearest Neighbor Graphs. SISAP Camilla Birch Okkels, Martin Aumüller, Arthur Zimek
2024	B	`conf`	Overview of the SISAP 2024 Indexing Challenge. SISAP Eric Sadit Tellez, Martin Aumüller, Vladimir Mic
2024	J	`jnl`	PLAN: Variance-Aware Private Mean Estimation. Proc. Priv. Enhancing Technol. Martin Aumüller, Christian Janos Lebeda, Boel Nelson, Rasmus Pagh
2024	J	`jnl`	Results of the Big ANN: NeurIPS'23 competition. CoRR 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
2023	B	`conf`	Overview of the SISAP 2023 Indexing Challenge. SISAP Eric Sadit Tellez, Martin Aumüller, Edgar Chávez
2023	J	`jnl`	PLAN: Variance-Aware Private Mean Estimation. CoRR Martin Aumüller, Christian Janos Lebeda, Boel Nelson, Rasmus Pagh
2023	J	`jnl`	Recent Approaches and Trends in Approximate Nearest Neighbor Search, with Remarks on Benchmarking. IEEE Data Eng. Bull. Martin Aumüller, Matteo Ceccarello
2023	B	`conf`	Solving k-Closest Pairs in High-Dimensional Data. SISAP Martin Aumüller, Matteo Ceccarello
2023	B	`conf`	Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback. SISAP Omar Shahbaz Khan, Martin Aumüller, Björn Þór Jónsson
2022	A	`conf`	DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search. AISTATS Matti Karppa, Martin Aumüller, Rasmus Pagh
2022	B	`conf`	Implementing Distributed Similarity Joins using Locality Sensitive Hashing. EDBT Martin Aumüller, Matteo Ceccarello
2022	J	`jnl`	Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access. J. Priv. Confidentiality Christian Janos Lebeda, Martin Aumüller, Rasmus Pagh
2022	J	`jnl`	Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. CoRR 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
2022	J	`jnl`	Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All? ACM Trans. Database Syst. Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
2022	J	`jnl`	Sampling near neighbors in search for fairness. Commun. ACM Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
2021	J	`jnl`	DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search. CoRR Matti Karppa, Martin Aumüller, Rasmus Pagh
2021	A*	`conf`	Differentially Private Sparse Vectors with Low Error, Optimal Space, and Fast Access. CCS Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh
2021	J	`jnl`	Differentially private sparse vectors with low error, optimal space, and fast access. CoRR Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh
2021	J	`jnl`	Fair near neighbor search via sampling. SIGMOD Rec. Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
2021	—	`conf`	Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. NeurIPS (Competition and Demos) 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
2021	J	`jnl`	Sampling a Near Neighbor in High Dimensions - Who is the Fairest of Them All? CoRR Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
2021	J	`jnl`	The role of local dimensionality measures in benchmarking nearest neighbor search. Inf. Syst. Martin Aumüller, Matteo Ceccarello
2020	J	`jnl`	ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms. Inf. Syst. Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
2020	B	`conf`	Algorithm Engineering for High-Dimensional Similarity Search Problems (Invited Talk). SEA Martin Aumüller
2020	B	`conf`	Differentially Private Sketches for Jaccard Similarity Estimation. SISAP Martin Aumüller, Anders Bourgeat, Jana Schmurr
2020	J	`jnl`	Differentially Private Sketches for Jaccard Similarity Estimation. CoRR Martin Aumüller, Anders Bourgeat, Jana Schmurr
2020	A*	`conf`	Fair Near Neighbor Search: Independent Range Sampling in High Dimensions. PODS Martin Aumüller, Rasmus Pagh, Francesco Silvestri
2020	A*	`conf`	Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN. ACM Multimedia Quoc-Tuan Truong, Hady W. Lauw, Martin Aumüller, Naoko Nitta
2020	B	`conf`	Running Experiments with Confidence and Sanity. SISAP Martin Aumüller, Matteo Ceccarello
2020	B	`ed.`	Similarity Search and Applications - 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 - October 2, 2020, Proceedings SISAP Shin'ichi Satoh, Lucia Vadicamo, Arthur Zimek, Fabio Carrara, Ilaria Bartolini, Martin Aumüller, Björn Þór Jónsson, Rasmus Pagh
2019	—	`conf`	Benchmarking Nearest Neighbor Search: Influence of Local Intrinsic Dimensionality and Result Diversity in Real-World Datasets. EDML@SDM Martin Aumüller, Matteo Ceccarello
2019	J	`jnl`	Dual-Pivot Quicksort: Optimality, Analysis and Zeros of Associated Lattice Paths. Comb. Probab. Comput. Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
2019	J	`jnl`	Fair Near Neighbor Search: Independent Range Sampling in High Dimensions. CoRR Martin Aumüller, Rasmus Pagh, Francesco Silvestri
2019	A	`conf`	PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors. ESA Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli
2019	J	`jnl`	PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors. CoRR Martin Aumüller, Tobias Christiani, Rasmus Pagh, Michael Vesterli
2019	A	`conf`	Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme. ALENEX Martin Aumüller, Nikolaj Hass
2019	B	`conf`	The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search. SISAP Martin Aumüller, Matteo Ceccarello
2019	J	`jnl`	The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search. CoRR Martin Aumüller, Matteo Ceccarello
2018	J	`jnl`	ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms. CoRR Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
2018	A*	`conf`	Distance-Sensitive Hashing. PODS Martin Aumüller, Tobias Christiani, Rasmus Pagh, Francesco Silvestri
2018	J	`jnl`	Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme. CoRR Martin Aumüller, Nikolaj Hass
2017	B	`conf`	ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms. SISAP Martin Aumüller, Erik Bernhardsson, Alexander John Faithfull
2017	J	`jnl`	Distance-sensitive hashing. CoRR Martin Aumüller, Tobias Christiani, Rasmus Pagh, Francesco Silvestri
2017	A*	`conf`	Parameter-free Locality Sensitive Hashing for Spherical Range Reporting. SODA Thomas D. Ahle, Martin Aumüller, Rasmus Pagh
2017	J	`jnl`	Theory and Applications of Hashing (Dagstuhl Seminar 17181). Dagstuhl Reports Martin Dietzfelbinger, Michael Mitzenmacher, Rasmus Pagh, David P. Woodruff, Martin Aumüller
2016	J	`jnl`	A Simple Hash Class with Strong Randomness Properties in Graphs and Hypergraphs. CoRR Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
2016	J	`jnl`	Counting Zeros in Random Walks on the Integers and Analysis of Optimal Dual-Pivot Quicksort. CoRR Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
2016	J	`jnl`	Dual-Pivot Quicksort: Optimality, Analysis and Zeros of Associated Lattice Paths. CoRR Martin Aumüller, Martin Dietzfelbinger, Clemens Heuberger, Daniel Krenn, Helmut Prodinger
2016	J	`jnl`	High-dimensional Spherical Range Reporting by Output-Sensitive Multi-Probing LSH. CoRR Thomas D. Ahle, Martin Aumüller, Rasmus Pagh
2016	J	`jnl`	How Good Is Multi-Pivot Quicksort? ACM Trans. Algorithms Martin Aumüller, Martin Dietzfelbinger, Pascal Klaue
2016	J	`jnl`	Optimal Partitioning for Dual-Pivot Quicksort. ACM Trans. Algorithms Martin Aumüller, Martin Dietzfelbinger
2015	J	`jnl`	How Good is Multi-Pivot Quicksort? CoRR Martin Aumüller, Martin Dietzfelbinger, Pascal Klaue
2015	—	`—`	On the Analysis of Two Fundamental Randomized Algorithms - Multi-Pivot Quicksort and Efficient Hash Functions. Martin Aumüller
2014	J	`jnl`	Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash. Algorithmica Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
2013	J	`jnl`	Optimal Partitioning for Dual Pivot Quicksort CoRR Martin Aumüller, Martin Dietzfelbinger
2013	—	`conf`	Optimal Partitioning for Dual Pivot Quicksort - (Extended Abstract). ICALP (1) Martin Aumüller, Martin Dietzfelbinger
2012	J	`jnl`	Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash CoRR Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
2012	A	`conf`	Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash. ESA Martin Aumüller, Martin Dietzfelbinger, Philipp Woelfel
2009	A	`conf`	Experimental Variations of a Theoretically Good Retrieval Data Structure. ESA Martin Aumüller, Martin Dietzfelbinger, Michael Rink