Markus Schneider

Orcid: 0000-0003-0543-2593

Affiliations:
  • University of Ulm, Germany
  • Ravensburg-Weingarten University of Applied Sciences, Autonomous Mobile Service Robots Laboratory, Weingarten, Germany


According to our database1, Markus Schneider authored at least 20 papers between 2009 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Multi-label semantic segmentation of magnetic resonance images of the prostate gland.
Discov. Artif. Intell., 2024

Instance Segmentation with a Novel Tree Log Detection Dataset.
Proceedings of the KI 2024: Advances in Artificial Intelligence, 2024

A Note on Linear Time Series Prediction.
Proceedings of the KI 2024: Advances in Artificial Intelligence, 2024

2023
A Novel Approach to Spectral Estimation and Moving Average Model Parameter Estimation.
IEEE Signal Process. Lett., 2023

2022
Cyclic Nonlinear Correlation Analysis for Time Series.
IEEE Access, 2022

Singular Spectrum Analysis and Circulant Maximum Variance Frames.
Adv. Data Sci. Adapt. Anal., 2022

Structured Nonlinear Discriminant Analysis.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
κ-Circulant Maximum Variance Bases.
Proceedings of the KI 2021: Advances in Artificial Intelligence - 44th German Conference on AI, Virtual Event, September 27, 2021

Comparison of Anomaly Detection and Solution Strategies for Household Service Robotics using Knowledge Graphs.
Proceedings of the 3rd IEEE International Conference on Artificial Intelligence in Engineering and Technology, 2021

2017
Expected similarity estimation for large-scale anomaly detection.
PhD thesis, 2017

2016
Expected similarity estimation for large-scale batch and streaming anomaly detection.
Mach. Learn., 2016

Constant Time EXPected Similarity Estimation for Large-Scale Anomaly Detection.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Constant Time EXPected Similarity Estimation using Stochastic Optimization.
CoRR, 2015

Kernel Feature Maps from Arbitrary Distance Metrics.
Proceedings of the KI 2015: Advances in Artificial Intelligence, 2015

Expected similarity estimation for large scale anomaly detection.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
LAT: A simple Learning from Demonstration method.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

Transductive Learning for Multi-Task Copula Processes.
Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

2010
Robot Learning by Demonstration with local Gaussian process regression.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Combining Gaussian Processes and Conventional Path Planning in a Learning from Demonstration Framework.
Proceedings of the Research and Education in Robotics - EUROBOT 2010, 2010

2009
The Teaching-Box: A universal robot learning framework.
Proceedings of the 14th International Conference on Advanced Robotics, 2009


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