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Publications of Author

1. Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
   Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach. [Citation Graph (0, 0)][DBLP]
   Artificial Intelligence and Applications, 2006, pp:428-433 [Conf]
   
2. Daniel Schneegaß, Thomas Martinetz, Michael Clausohm
   OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. [Citation Graph (0, 0)][DBLP]
   ESANN, 2006, pp:575-580 [Conf]
   
3. Thomas Martinetz, Kai Labusch, Daniel Schneegaß
   SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. [Citation Graph (0, 0)][DBLP]
   ICANN (2), 2005, pp:301-306 [Conf]
   
4. Daniel Schneegaß, Kai Labusch, Thomas Martinetz
   MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. [Citation Graph (0, 0)][DBLP]
   ICANN (1), 2006, pp:150-158 [Conf]
   
5. Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
   Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification. [Citation Graph (0, 0)][DBLP]
   ICANN (1), 2007, pp:109-118 [Conf]
   
6. 
   Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. [Citation Graph (, )][DBLP]
   
   
7. 
   Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. [Citation Graph (, )][DBLP]
   
   
8. 
   The Intrinsic Recurrent Support Vector Machine. [Citation Graph (, )][DBLP]
   
   
9. 
   Safe exploration for reinforcement learning. [Citation Graph (, )][DBLP]
   
   
10. 
    A Neural Reinforcement Learning Approach to Gas Turbine Control. [Citation Graph (, )][DBLP]
    
    
11. 
    Uncertainty propagation for quality assurance in Reinforcement Learning. [Citation Graph (, )][DBLP]