Daniel Schneegaß

According to our database1, Daniel Schneegaß authored at least 17 papers between 2005 and 2020.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
RelSen: An Optimization-based Framework for Simultaneous Sensor Reliability Monitoring and Process State Estimation.
CoRR, 2020

RelSen: An Optimization-based Framework for Simultaneously Sensor Reliability Monitoring and Data Cleaning.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
A Search for the Underlying Equation Governing Similar Systems.
CoRR, 2019

2009
SoftDoubleMaxMinOver: Perceptron-Like Training of Support Vector Machines.
IEEE Trans. Neural Networks, 2009

On the bias of batch Bellman residual minimisation.
Neurocomputing, 2009

2008
Steigerung der Informationseffizienz im Reinforcement-Learning.
PhD thesis, 2008

Uncertainty propagation for quality assurance in Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2008

Safe exploration for reinforcement learning.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007
A Neural Reinforcement Learning Approach to Gas Turbine Control.
Proceedings of the International Joint Conference on Neural Networks, 2007

Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification.
Proceedings of the Artificial Neural Networks, 2007

Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

The Intrinsic Recurrent Support Vector Machine.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006
MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation.
Proceedings of the Artificial Neural Networks, 2006

OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2006

2005
SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005


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