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Optimization of the Backpropagation Algorithm for Training Multilayer Perceptrons - (September 1994) Authors W. Schiffmann, M. Joost, R. Werner Language English Type public Url Summary Comparison of algorithms Pages 36 Parts 1 Introduction 2 Application 3 Mathematical Notation 4 Backpropagation 5 Global Learning Rate Adaptation 6 Lobal Learning Rate Adaptations 7 Conclusion 8 References

Comparison of Optimized Backpropagation Algorithms - (1993) Authors W. Schiffmann, M. Joost, R. Werner Language English Type public Url Summary Comparison of algorithms on hard practical classification tasks, big medical data sets. Pages 8 Parts 1 Introduction 2 Thyroid-Data 3 Standard Backpropagation 4 Online Training 5 Batched Training 6 Conclusion 7 References

An Empirical Study of Learning Speed In Back-Propagation Networks - (September 1988) Authors Scott E. Fahlman Language English Type public Url Summary Backpropagation benchmarks, quickprop, scaling Pages 17 Parts 1 Introduction 2 Methodology 3 Experiments and Results 4 Conclusions and Future Work

A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm - (1993) Authors Martin Riedmiller, Heinrich Braun Language English Type public Url Summary Rprop learning algorithm, faster backpropagation Pages 6 Parts 1 Introduction 2 RPROP 3 Results 4 Conclusion

Improving the Rprop Learning Algorithm - (2000) Authors Christian Igel, Michael Huesken Language English Type public Url Summary Supervised learning, individual step-size adaptation, weight back-tracking, Rprop Pages 7 Parts 1 Introduction 2 The Rprop Algorithm 3 Modifications 4 Experimental Evaluation 5 Conclusion

Speeding up Backpropagation Algorithms by using Cross-Entropy Combined with Pattern Normalization - (1997) Authors Merten Joost, Wolfram Schiffmann Language English Type public Url Summary cross entropy vs. quadratic error function, pattern normalization, CEN-optimization Pages 10 Parts 1 Introduction 2 Deception by the SSE 3 Network Training from the Statistical Point of View 4 Cross Entropy (CE) as an Error Function 5 Normalization of the Input Vectors 6 Simulation Results