Martin Aumüller

712 total citations
15 papers, 188 citations indexed

About

Martin Aumüller is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Martin Aumüller has authored 15 papers receiving a total of 188 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 5 papers in Computer Networks and Communications. Recurrent topics in Martin Aumüller's work include Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (5 papers) and Data Management and Algorithms (4 papers). Martin Aumüller is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (5 papers) and Data Management and Algorithms (4 papers). Martin Aumüller collaborates with scholars based in Denmark, Italy and United States. Martin Aumüller's co-authors include Alexander Faithfull, Martin Dietzfelbinger, Rasmus Pagh, Francesco Silvestri, Philipp Woelfel, Sepideh Mahabadi, Sariel Har-Peled, Francesco Silvestri, Hady W. Lauw and Quoc-Tuan Truong and has published in prestigious journals such as SHILAP Revista de lepidopterología, Communications of the ACM and ACM SIGMOD Record.

In The Last Decade

Martin Aumüller

13 papers receiving 175 citations

Peers

Martin Aumüller

CVPR

CNC

Alexander Faithfull Denmark

Yury Lifshits United States

Jiajun Liu China

Andrey Logvinov Russia

Luisa Micó Spain

El Houssine Bouyakhf Morocco

Thijs Laarhoven Netherlands

Han Xiao China

Miquel Ferrer Spain

Ahmed Salem China

Alexander Faithfull Denmark

Martin Aumüller

76 ×0.8

CVPR

57 ×0.7

45 ×0.7

18 ×0.6

CNC

20 ×1.2

Citations per year, relative to Martin Aumüller Martin Aumüller (= 1×) peers Alexander Faithfull

Countries citing papers authored by Martin Aumüller

Since Specialization

Citations

This map shows the geographic impact of Martin Aumüller's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Aumüller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Aumüller more than expected).

Fields of papers citing papers by Martin Aumüller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Aumüller. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Aumüller. The network helps show where Martin Aumüller may publish in the future.

Co-authorship network of co-authors of Martin Aumüller

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Aumüller. A scholar is included among the top collaborators of Martin Aumüller based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Aumüller. Martin Aumüller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Aumüller, Martin, et al.. (2024). PLAN: Variance-Aware Private Mean Estimation. Proceedings on Privacy Enhancing Technologies. 2024(3). 606–625.

Aumüller, Martin, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, & Francesco Silvestri. (2022). Sampling a Near Neighbor in High Dimensions. Research Padua Archive (University of Padua). 3 indexed citations

Aumüller, Martin, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, & Francesco Silvestri. (2022). Sampling near neighbors in search for fairness. Communications of the ACM. 65(8). 83–90. 4 indexed citations

Aumüller, Martin, et al.. (2022). Implementing Distributed Similarity Joins using Locality Sensitive Hashing. IT University Of Copenhagen (IT University of Copenhagen).

Aumüller, Martin, et al.. (2022). Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access. SHILAP Revista de lepidopterología. 12(2). 1 indexed citations

Aumüller, Martin, et al.. (2021). The role of local dimensionality measures in benchmarking nearest neighbor search. Information Systems. 101. 101807–101807. 11 indexed citations

Aumüller, Martin, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, & Francesco Silvestri. (2021). Fair near neighbor search via sampling. ACM SIGMOD Record. 50(1). 42–49. 9 indexed citations

Truong, Quoc-Tuan, Hady W. Lauw, Martin Aumüller, & Naoko Nitta. (2020). Reproducibility Companion Paper: Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN. IT University Of Copenhagen (IT University of Copenhagen). 4444–4447. 1 indexed citations

Aumüller, Martin, et al.. (2019). PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 3 indexed citations

10.

Aumüller, Martin, et al.. (2019). Benchmarking Nearest Neighbor Search: Influence of Local Intrinsic Dimensionality and Result Diversity in Real-World Datasets.. IT University Of Copenhagen (IT University of Copenhagen). 14–23. 1 indexed citations

11.

Aumüller, Martin, et al.. (2019). ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms. Information Systems. 87. 101374–101374. 125 indexed citations

12.

Aumüller, Martin, et al.. (2018). Distance-Sensitive Hashing. IT University Of Copenhagen (IT University of Copenhagen). 89–104. 10 indexed citations

13.

Aumüller, Martin, et al.. (2016). How Good Is Multi-Pivot Quicksort?. ACM Transactions on Algorithms. 13(1). 1–47. 5 indexed citations

14.

Aumüller, Martin & Martin Dietzfelbinger. (2015). Optimal Partitioning for Dual-Pivot Quicksort. ACM Transactions on Algorithms. 12(2). 1–36. 6 indexed citations

15.

Aumüller, Martin, Martin Dietzfelbinger, & Philipp Woelfel. (2013). Explicit and Efficient Hash Families Suffice for Cuckoo Hashing with a Stash. Algorithmica. 70(3). 428–456. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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