Active Bibliography

An Investigation of the Gradient Descent Process in Neural Networks – Barak A. Pearlmutter - 1996
12 Efficient Training of Feed-Forward Neural Networks – Martin Møller - 1997
125 Efficient BackProp – Yann Lecun, Leon Bottou, Genevieve B. Orr, Klaus-Robert Müller - 1998
27 Computing Second Derivatives in Feed-Forward Networks: a Review – Wray Buntine, Andreas S. Weigend - 1994
135 Gradient calculation for dynamic recurrent neural networks: a survey – Barak A. Pearlmutter - 1995
50 Discovering Neural Nets With Low Kolmogorov Complexity And High Generalization Capability – Jürgen Schmidhuber - 1997
16 Discovering Problem Solutions with Low Kolmogorov Complexity and High Generalization Capability – Jürgen Schmidhuber - 1994
1 Recurrent Neural Networks for Adaptive Temporal Processing – Yoshua Bengio, Paolo Frasconi, Marco Gori - 1993
ARTIFICIAL NEURAL NETWORKS IN HYDROLOGY. I: PRELIMINARY CONCEPTS – n.n.
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
51 Reinforcement Learning And Its Application To Control – Vijaykumar Gullapalli - 1992
11 An Efficient MDL-Based Construction of RBF Networks – Ales Leonardis, Horst Bischof, Horst Bischof - 1998
19 An Anytime Approach To Connectionist Theory Refinement: Refining The Topologies Of Knowledge-Based Neural Networks – David William Opitz - 1995
7 Optimal Learning in Artificial Neural Networks: A Theoretical View – M. Bianchini, M. Gori
1 On-Line Stochastic Functional Smoothing Optimization for Neural Network Training – Chuan Wang, Jose C. Principe, Dr. Jose, C. Principe, Ph. D - 1997
27 Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods – G. D. Magoulas, M. N. Vrahatis, G. S. Androulakis - 1999
6 Deterministic Nonmonotone Strategies for Effective Training of Multilayer Perceptrons – Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis
ADAPTIVE ALGORITHMS FOR NEURAL NETWORK SUPERVISED LEARNING: A DETERMINISTIC OPTIMIZATION APPROACH – George D. Magoulas, Michael N. Vrahatis - 2005
126 First and Second-Order Methods for Learning: between Steepest Descent and Newton's Method – Roberto Battiti - 1992