Maximilian von Zastrow

Orcid: 0000-0001-9848-3714

According to our database1, Maximilian von Zastrow authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
CoMadOut - a robust outlier detection algorithm based on CoMAD.
Mach. Learn., October, 2024

X Marks the Spot? Applying Recent Keypoint Detection Methods to Paleozoological Landmarking.
Proceedings of the 20th IEEE International Conference on e-Science, 2024

There is Strength in Numbers: A Comprehensive Study of Machine Learning Algorithms for Sex Identification on Animal Bone Remains.
Proceedings of the 20th IEEE International Conference on e-Science, 2024

An Exploratory Case Study on Data Breach Journalism.
Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024

2023
Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study.
Adv. Data Anal. Classif., March, 2023

Advances in Unsupervised Learning and Applications: Background knowledge driven subspace clustering, semantic password guessing and learned index structures.
PhD thesis, 2023

A Simple and Explainable Method for Uncertainty Estimation using Attribute Prototype Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Stirring the Pot - Teaching Reinforcement Learning Agents a "Push-Your-Luck" board game.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

SePass: Semantic Password Guessing Using k-nn Similarity Search in Word Embeddings.
Proceedings of the Advanced Data Mining and Applications - 18th International Conference, 2022

2021
Towards a Learned Index Structure for Approximate Nearest Neighbor Search Query Processing.
Proceedings of the Similarity Search and Applications - 14th International Conference, 2021

AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval.
Proceedings of the LWDA 2021 Workshops: FGWM, 2021

OAB - An Open Anomaly Benchmark Framework for Unsupervised and Semisupervised Anomaly Detection on Image and Tabular Data Sets.
Proceedings of the 2021 International Conference on Data Mining, 2021

Implicit Hough Transform Neural Networks for Subspace Clustering.
Proceedings of the 2021 International Conference on Data Mining, 2021

2019
On coMADs and Principal Component Analysis.
Proceedings of the Similarity Search and Applications - 12th International Conference, 2019

SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge.
Proceedings of the Similarity Search and Applications - 12th International Conference, 2019

CODEC - Detecting Linear Correlations in Dense Clusters using coMAD-based PCA.
Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", Berlin, Germany, September 30, 2019


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