-
1
-
-
0001024110
-
First and Second Order Methods for Learning: Between Steepest Descent and Newton's Method
-
Battiti, R. (1992). First and Second Order Methods for Learning: Between Steepest Descent and Newton's Method, Neural Computation, 4, 141-166.
-
(1992)
Neural Computation
, vol.4
, pp. 141-166
-
-
Battiti, R.1
-
2
-
-
0002906163
-
Improving the convergence of back-propagation learning with second order methods
-
Touretzky, D., Hinton, G. and Sejnowski, T. (Eds.). San Mateo, CA: Morgan kaufmann
-
Becker, S. and Le Cun, Y. (1989). Improving the convergence of back-propagation learning with second order methods. In Touretzky, D., Hinton, G. and Sejnowski, T. (Eds.). Proceedings of the 1988 Connectionist Models Summer School (pp.29-37). San Mateo, CA: Morgan kaufmann.
-
(1989)
Proceedings of the 1988 Connectionist Models Summer School
, pp. 29-37
-
-
Becker, S.1
Le Cun, Y.2
-
3
-
-
0023540353
-
Successfully using Peak Learning Rates of 10 (and greater) in the Back-Propagation Networks with the HEURISTIC Llearning Algorithm
-
CA
-
Carter, J. P. (1987). Successfully using Peak Learning Rates of 10 (and greater) in the Back-Propagation Networks with the HEURISTIC Llearning Algorithm, Proceedings of IEEE, Ist Int. Conf. on NN, San Diego, CA, pp. 645-651.
-
(1987)
Proceedings of IEEE, Ist Int. Conf. on NN, San Diego
, pp. 645-651
-
-
Carter, J.P.1
-
4
-
-
38249001690
-
A Gradient Range Bases Heuristic Algorithm for Back
-
Evans, D. J. and Sanossian, H. Y. Y. (1993). A Gradient Range Bases Heuristic Algorithm for Back. Propagation, J. of Microcomputer Application, 16, pp. 179-188.
-
(1993)
Propagation, J. of Microcomputer Application
, vol.16
, pp. 179-188
-
-
Evans, D.J.1
Sanossian, H.Y.Y.2
-
5
-
-
0003000735
-
Faster Learning Varitation on Back Propagation. An Empirical Study
-
Kaufman
-
Fahlman, S.E (1989). Faster Learning Varitation on Back Propagation. An Empirical Study, Proceedings of the 1988 Connectionist Models, Kaufman, pp.38-51.
-
(1989)
Proceedings of the 1988 Connectionist Models
, pp. 38-51
-
-
Fahlman, S.E.1
-
6
-
-
0024124741
-
Improving the Learning Rate of Back-Propagation with the Gradient Reuse Algorithm
-
san Diego, CA
-
Hush, D. R. and Salas, J. M. Improving the Learning Rate of Back-Propagation with the Gradient Reuse Algorithm, IEEE Int. Conf. on neural Networks, 1, pp. 441-447, san Diego, CA.
-
IEEE Int. Conf. on Neural Networks
, vol.1
, pp. 441-447
-
-
Hush, D.R.1
Salas, J.M.2
-
7
-
-
0024137490
-
Increased Rates of Convergence through Learning Rate Adaptation
-
Jacobs, R. A. (1988). Increased Rates of Convergence through Learning Rate Adaptation, Neural Networks, 1(4), 295-308.
-
(1988)
Neural Networks
, vol.1
, Issue.4
, pp. 295-308
-
-
Jacobs, R.A.1
-
8
-
-
0002290223
-
Efficient parallel learning algorithms for neural networks
-
Touretzky, D. S. (Ed.), San Mateo, CA: Morgan Kaufmann
-
Kramer, A. H. and Sangiovanni-Vincentelli, A. (1989) Efficient parallel learning algorithms for neural networks, In Touretzky, D. S. (Ed.), Advances in Neural Information systems 1, (pp.40-48). San Mateo, CA: Morgan Kaufmann.
-
(1989)
Advances in Neural Information Systems
, vol.1
, pp. 40-48
-
-
Kramer, A.H.1
Sangiovanni-Vincentelli, A.2
-
9
-
-
0003794792
-
Experiments on Learning Back Propagation
-
Carnegie-Mellon University, Pittusburg, PA
-
Plaut, D. C., Nowlan, S. J. and Hinton, G. E. (1989). Experiments on Learning Back Propagation, Technical Report CMU-CS, 86-126, Carnegie-Mellon University, Pittusburg, PA.
-
(1989)
Technical Report CMU-CS, 86-126
-
-
Plaut, D.C.1
Nowlan, S.J.2
Hinton, G.E.3
-
10
-
-
0000646059
-
Learning Internal Representations by Error Propagation
-
Rumelhart, D.E., McClelland, J.L., (eds.). MIT press, Cambridge, MA
-
Rumelhart, D. E., Hinton, G. E. and Williams, R. J. (1986). Learning Internal Representations by Error Propagation., In Rumelhart, D.E., McClelland, J.L., (eds.). Parallel Distributed Processing:Explorations in the Microstructure of Cognition, pp. 318-362. MIT press, Cambridge, MA.
-
(1986)
Parallel Distributed Processing:Explorations in the Microstructure of Cognition
, pp. 318-362
-
-
Rumelhart, D.E.1
Hinton, G.E.2
Williams, R.J.3
-
15
-
-
0028292832
-
Minimisation Methods for Training Feedforward Neural Networks
-
Van Der Smagt, P. P. (1994). Minimisation Methods for Training Feedforward Neural Networks, Neural Networks, 7(1), pp.1-11.
-
(1994)
Neural Networks
, vol.7
, Issue.1
, pp. 1-11
-
-
Van Der Smagt, P.P.1
-
16
-
-
0023541050
-
Learning Algorithms for Connectionist Networks:Applied Gradient Methods of Nonlinear Optimization
-
San Diego, CA
-
Watrous, R. L. (1987). Learning Algorithms for Connectionist Networks:Applied Gradient Methods of Nonlinear Optimization, Proceedings of the IEEE 1st International Conference on Neural Networks, San Diego, CA, pp. 619-627.
-
(1987)
Proceedings of the IEEE 1st International Conference on Neural Networks
, pp. 619-627
-
-
Watrous, R.L.1
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