-
1
-
-
0026953305
-
Improving generalization performance using double back-propagation
-
November
-
H. Drucker and Y. Le Cun. Improving generalization performance using double back-propagation. IEEE Transactions on Neural Networks, 3(6), November 1992.
-
(1992)
IEEE Transactions on Neural Networks
, vol.3
, pp. 6
-
-
Drucker, H.1
Le Cun, Y.2
-
2
-
-
0001440803
-
Tangent prop-A formalism for specifying selected invariances in an adaptive network
-
John E. Moody, Steve J. Hanson, and Richard P. Lippmann, editors, Morgan Kaufmann Publishers, Inc.
-
P. Simard, B. Victorri, Y. Le Cun, and J. Denker. Tangent prop-A formalism for specifying selected invariances in an adaptive network. In John E. Moody, Steve J. Hanson, and Richard P. Lippmann, editors, Advances in Neural Information Processing Systems, volume 4, pages 895-903. Morgan Kaufmann Publishers, Inc., 1992.
-
(1992)
Advances in Neural Information Processing Systems
, vol.4
, pp. 895-903
-
-
Simard, P.1
Victorri, B.2
Le Cun, Y.3
Denker, J.4
-
3
-
-
0008284357
-
On learning the derivatives of an unknown mapping with multilayer feedforward networks
-
Halbert White, editor, chapter 12, Blackwell, Cambridge, Mass.
-
H. White and A. R. Gallant. On learning the derivatives of an unknown mapping with multilayer feedforward networks. In Halbert White, editor, Artificial Neural Networks, chapter 12, pages 206-223. Blackwell, Cambridge, Mass., 1992.
-
(1992)
Artificial Neural Networks
, pp. 206-223
-
-
White, H.1
Gallant, A.R.2
-
4
-
-
0347697426
-
Universal approximation of an unknown mapping and its derivative
-
Halbert White, editor, chapter 6, Blackwell, Cambridge, Mass.
-
H. White, K. Hornik, and M. Stinchcombe. Universal approximation of an unknown mapping and its derivative. In Halbert White, editor, Artificial Neural Networks, chapter 6, pages 55-77. Blackwell, Cambridge, Mass., 1992.
-
(1992)
Artificial Neural Networks
, pp. 55-77
-
-
White, H.1
Hornik, K.2
Stinchcombe, M.3
-
5
-
-
0001053173
-
Prediction of chaotic time series with neural networks and the issues of dynamic modeling
-
J. Principe, A. Rathie, and J. Kuo. Prediction of chaotic time series with neural networks and the issues of dynamic modeling. Bifurcations and Chaos, 2(4), 1992.
-
(1992)
Bifurcations and Chaos
, vol.2
, pp. 4
-
-
Principe, J.1
Rathie, A.2
Kuo, J.3
-
6
-
-
0006978332
-
Dynamic modeling of chaotic time series
-
Russell Greiner, Thomas Petsche, and Stephen Jose Hanson, editors, volume IV of Making Learning Systems Practical, chapter 9, The MIT Press, Cambridge, Mass.
-
G. Deco and B. Schürmann. Dynamic modeling of chaotic time series. In Russell Greiner, Thomas Petsche, and Stephen Jose Hanson, editors, Computational Learning Theory and Natural Learning Systems, volume IV of Making Learning Systems Practical, chapter 9, pages 137-153. The MIT Press, Cambridge, Mass., 1997.
-
(1997)
Computational Learning Theory and Natural Learning Systems
, pp. 137-153
-
-
Deco, G.1
Schürmann, B.2
-
7
-
-
0002623785
-
Learning distributed representations of concepts
-
Hillsdale, NJ, Erlbaum
-
G. E. Hinton. Learning distributed representations of concepts. In Proc. Eigth Annual Conf. Cognitive Science Society, pages 1-12, Hillsdale, NJ, 1986. Erlbaum.
-
(1986)
Proc. Eigth Annual Conf. Cognitive Science Society
, pp. 1-12
-
-
Hinton, G.E.1
-
8
-
-
0000255539
-
Fast exact multiplication by the Hessian
-
Barak A. Pearlmutter. Fast exact multiplication by the Hessian. Neural Computation, 6(1):147-160,1994.
-
(1994)
Neural Computation
, vol.6
, Issue.1
, pp. 147-160
-
-
Pearlmutter, B.A.1
-
9
-
-
84899019609
-
Industrial strength modeling tools
-
Submitted to
-
G. W. Flake. Industrial strength modeling tools. Submitted to NIPS 99, 1999.
-
(1999)
NIPS 99
-
-
Flake, G.W.1
|