-
1
-
-
0003761887
-
-
Unpublished doctoral dissertation, Ecole Polytechnique Fédérale de Lausanne, Switzerland
-
Alpaydin, E. A. I. (1990). Neural models of supervised and unsupervised learning. Unpublished doctoral dissertation, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
-
(1990)
Neural Models of Supervised and Unsupervised Learning
-
-
Alpaydin, E.A.I.1
-
2
-
-
0012854245
-
Tilinglike learning in the parity machine
-
Biehl, M., & Opper, M. (1991). Tilinglike learning in the parity machine. Physical Review A, 44, 6888.
-
(1991)
Physical Review A
, vol.44
, pp. 6888
-
-
Biehl, M.1
Opper, M.2
-
3
-
-
0000876414
-
Local learning algorithms
-
Bottou, L., & Vapnik, V. (1992). Local learning algorithms. Neural Computation, 4(6), 888-900.
-
(1992)
Neural Computation
, vol.4
, Issue.6
, pp. 888-900
-
-
Bottou, L.1
Vapnik, V.2
-
4
-
-
0003495934
-
-
(Tech. Rep. No. 421). Berkeley: Department of Statistics, University of California at Berkeley
-
Breiman, L. (1994). Bagging predictors (Tech. Rep. No. 421). Berkeley: Department of Statistics, University of California at Berkeley.
-
(1994)
Bagging Predictors
-
-
Breiman, L.1
-
5
-
-
0003802343
-
-
Monterey, CA: Wadsworth and Brooks/Cole
-
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Monterey, CA: Wadsworth and Brooks/Cole.
-
(1984)
Classification and Regression Trees
-
-
Breiman, L.1
Friedman, J.H.2
Olshen, R.A.3
Stone, C.J.4
-
6
-
-
0000624304
-
Large automatic learning, rule extraction, and generalization
-
Denker, J., Schwartz, D., Wittner, B., Solla, S., Howard, R., Jackel, L., & Hopfield, J. (1987). Large automatic learning, rule extraction, and generalization. Complex Systems, 1, 877-922.
-
(1987)
Complex Systems
, vol.1
, pp. 877-922
-
-
Denker, J.1
Schwartz, D.2
Wittner, B.3
Solla, S.4
Howard, R.5
Jackel, L.6
Hopfield, J.7
-
8
-
-
0002552358
-
Improving performance in neural networks using a boosting algorithm
-
S. J. Hanson, J. D. Cowan, & C. L. Giles (Eds.) San Mateo, CA: Morgan Kaufmann
-
Drucker, H., Schapire, R., & Simard, P. (1993). Improving performance in neural networks using a boosting algorithm. In S. J. Hanson, J. D. Cowan, & C. L. Giles (Eds.), Advances in neural information processing systems, 5 (pp. 42-49). San Mateo, CA: Morgan Kaufmann.
-
(1993)
Advances in Neural Information Processing Systems
, vol.5
, pp. 42-49
-
-
Drucker, H.1
Schapire, R.2
Simard, P.3
-
9
-
-
0000155950
-
The cascade-correlation learning architecture
-
D. S. Touretzky (Ed.) San Mateo: Morgan Kaufmann
-
Fahlman, S. E., & Lebiere, C. (1990). The cascade-correlation learning architecture. In D. S. Touretzky (Ed.), Advances in neural information processing systems, 2 (pp. 524-532). San Mateo: Morgan Kaufmann.
-
(1990)
Advances in Neural Information Processing Systems
, vol.2
, pp. 524-532
-
-
Fahlman, S.E.1
Lebiere, C.2
-
10
-
-
0346502477
-
Speaker recognition using neural tree networks
-
J. D. Cowan, G. Tesauro, & J. Alspector (Eds.) San Mateo, CA: Morgan Kaufmann
-
Farrell, K. R., & Mammone, R. J. (1994). Speaker recognition using neural tree networks. In J. D. Cowan, G. Tesauro, & J. Alspector (Eds.), Advances in Neural Information Processing Systems, 6 (pp. 1035-1042). San Mateo, CA: Morgan Kaufmann.
-
(1994)
Advances in Neural Information Processing Systems
, vol.6
, pp. 1035-1042
-
-
Farrell, K.R.1
Mammone, R.J.2
-
11
-
-
0000783575
-
The Upstart algorithm: A method for constructing and training feedforward neural networks
-
Frean, M. (1990). The Upstart algorithm: A method for constructing and training feedforward neural networks. Neural Computation, 2(2), 198-209.
-
(1990)
Neural Computation
, vol.2
, Issue.2
, pp. 198-209
-
-
Frean, M.1
-
12
-
-
0007133880
-
A "thermal" perceptronlearning rule
-
Frean, M. (1992). A "thermal" perceptronlearning rule. Neural Computation, 4(6), 946-957.
-
(1992)
Neural Computation
, vol.4
, Issue.6
, pp. 946-957
-
-
Frean, M.1
-
13
-
-
0003483421
-
-
(Tech. Rep.) Stanford, CA: Department of Statistics, Stanford University
-
Friedman, J. H. (1996). On bias, variance, 0/1-loss, and the curse-of-dimensionality (Tech. Rep.) Stanford, CA: Department of Statistics, Stanford University.
-
(1996)
On Bias, Variance, 0/1-loss, and the Curse-of-dimensionality
-
-
Friedman, J.H.1
-
14
-
-
0347763086
-
Supervised learning with growing cell structures
-
J. D. Cowan, G. Tesauro, & J. Alspector (Eds.) San Mateo, CA: Morgan Kaufmann
-
Fritzke, B. (1994). Supervised learning with growing cell structures. In J. D. Cowan, G. Tesauro, & J. Alspector (Eds.), Advances in neural information processing systems, 6 (pp. 255-262). San Mateo, CA: Morgan Kaufmann.
-
(1994)
Advances in Neural Information Processing Systems
, vol.6
, pp. 255-262
-
-
Fritzke, B.1
-
17
-
-
0001942829
-
Neural networks and the bias/variance dilemma
-
Geman, S., Bienenstock, E., & Doursat, R. (1992). Neural networks and the bias/variance dilemma. Neural Computation, 4(1), 1-58.
-
(1992)
Neural Computation
, vol.4
, Issue.1
, pp. 1-58
-
-
Geman, S.1
Bienenstock, E.2
Doursat, R.3
-
18
-
-
0000854380
-
Rule-based neural networks for classification and probability estimation
-
Goodman, R. M., Smyth, P., Higgins, C. M., & Miller, J. W. (1992). Rule-based neural networks for classification and probability estimation. Neural Computation, 4(6), 781-804.
-
(1992)
Neural Computation
, vol.4
, Issue.6
, pp. 781-804
-
-
Goodman, R.M.1
Smyth, P.2
Higgins, C.M.3
Miller, J.W.4
-
19
-
-
0029768201
-
A convergence theorem for incremental learning with real-valued inputs
-
Gordon, M. B. (1996). A convergence theorem for incremental learning with real-valued inputs. In IEEE International Conference on Neural Networks, pp. 381-386.
-
(1996)
IEEE International Conference on Neural Networks
, pp. 381-386
-
-
Gordon, M.B.1
-
20
-
-
0012809439
-
Minimerror: A perceptron learning rule that finds the optimal weights
-
M. Verleysen (Ed.) Brussels: D Facto
-
Gordon, M. B., & Berchier, D. (1993). Minimerror: A perceptron learning rule that finds the optimal weights. In M. Verleysen (Ed.), European Symposium on Artificial Neural Networks (pp. 105-110). Brussels: D Facto.
-
(1993)
European Symposium on Artificial Neural Networks
, pp. 105-110
-
-
Gordon, M.B.1
Berchier, D.2
-
21
-
-
84956263536
-
Optimal learning with a temperature dependent algorithm
-
Gordon, M. B., & Grempel, D. (1995). Optimal learning with a temperature dependent algorithm. Europhysics Letters, 29(3), 257-262.
-
(1995)
Europhysics Letters
, vol.29
, Issue.3
, pp. 257-262
-
-
Gordon, M.B.1
Grempel, D.2
-
22
-
-
84956267329
-
Learning algorithms for perceptrons from statistical physics
-
Gordon, M. B., Peretto, P., & Berchier, D. (1993). Learning algorithms for perceptrons from statistical physics. Journal of Physics I (France), 3, 377-387.
-
(1993)
Journal of Physics I (France)
, vol.3
, pp. 377-387
-
-
Gordon, M.B.1
Peretto, P.2
Berchier, D.3
-
23
-
-
0023843391
-
Analysis of hidden units in a layered network trained to classify sonar targets
-
Gorman, R. P., & Sejnowski, T. J. (1988). Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks, 1, 75-89.
-
(1988)
Neural Networks
, vol.1
, pp. 75-89
-
-
Gorman, R.P.1
Sejnowski, T.J.2
-
24
-
-
0002885302
-
Statistical theory of learning a rule
-
W. K. Theumann & R. Koeberle (Eds.) Singapore: World Scientific
-
Gyorgyi, G., & Tishby, N. (1990). Statistical theory of learning a rule. In W. K. Theumann & R. Koeberle (Eds.), Neural networks and spin glasses. Singapore: World Scientific.
-
(1990)
Neural Networks and Spin Glasses
-
-
Gyorgyi, G.1
Tishby, N.2
-
26
-
-
0003250435
-
Single-layer learning revisited: A stepwise procedure for building and training a neural network
-
J. Hérault & F. Fogelman (Eds.) Berlin: Springer-Verlag
-
Knerr, S., Personnaz, L., & Dreyfus, G. (1990). Single-layer learning revisited: A stepwise procedure for building and training a neural network. In J. Hérault & F. Fogelman (Eds.), Neurocomputing, algorithms, architectures and applications (pp. 41-50). Berlin: Springer-Verlag.
-
(1990)
Neurocomputing, Algorithms, Architectures and Applications
, pp. 41-50
-
-
Knerr, S.1
Personnaz, L.2
Dreyfus, G.3
-
27
-
-
84956226983
-
A convergence theorem for sequential learning in two-layer perceptrons
-
Marchand, M., Golea, M., & Ruján, P. (1990). A convergence theorem for sequential learning in two-layer perceptrons. Europhysics Letters, 11, 487-492.
-
(1990)
Europhysics Letters
, vol.11
, pp. 487-492
-
-
Marchand, M.1
Golea, M.2
Ruján, P.3
-
28
-
-
84956068504
-
The offset algorithm: Building and learning method for multilayer neural networks
-
Martinez, D., & Estève, D. (1992). The offset algorithm: Building and learning method for multilayer neural networks. Europhysics Letters, 18, 95-100.
-
(1992)
Europhysics Letters
, vol.18
, pp. 95-100
-
-
Martinez, D.1
Estève, D.2
-
29
-
-
36149031331
-
Learning in feedforward layered networks: The Tiling algorithm
-
Mézard, M., & Nadal, J.-P. (1989). Learning in feedforward layered networks: The Tiling algorithm. J. Phys. A: Math. and Gen., 22, 2191-2203.
-
(1989)
J. Phys. A: Math. and Gen.
, vol.22
, pp. 2191-2203
-
-
Mézard, M.1
Nadal, J.-P.2
-
30
-
-
0042474533
-
A polynomial time algorithm for generating neural networks for pattern classification: Its stability properties and some test results
-
Mukhopadhyay, S., Roy, A., Kim, L. S., & Govil, S. (1993). A polynomial time algorithm for generating neural networks for pattern classification: Its stability properties and some test results. Neural Computation, 5(2), 317-330.
-
(1993)
Neural Computation
, vol.5
, Issue.2
, pp. 317-330
-
-
Mukhopadhyay, S.1
Roy, A.2
Kim, L.S.3
Govil, S.4
-
31
-
-
0001958391
-
Study of a growth algorithm for a feedforward neural network
-
Nadal, J.-P. (1989). Study of a growth algorithm for a feedforward neural network. Int. J. Neur. Syst., 1, 55-59.
-
(1989)
Int. J. Neur. Syst.
, vol.1
, pp. 55-59
-
-
Nadal, J.-P.1
-
33
-
-
0029411591
-
Learning and generalization with Minimerror, a temperature dependent learning algorithm
-
Raffin, B., & Gordon, M. B. (1995). Learning and generalization with Minimerror, a temperature dependent learning algorithm. Neural Computation, 7(6), 1206-1224.
-
(1995)
Neural Computation
, vol.7
, Issue.6
, pp. 1206-1224
-
-
Raffin, B.1
Gordon, M.B.2
-
34
-
-
0020415469
-
A neural model for category learning
-
Reilly, D. E, Cooper, L. N., & Elbaum, C. (1982). A neural model for category learning. Biological Cybernetics, 45, 35-41.
-
(1982)
Biological Cybernetics
, vol.45
, pp. 35-41
-
-
Reilly, D.E.1
Cooper, L.N.2
Elbaum, C.3
-
35
-
-
0027259956
-
A polynomial time algorithm for the construction and training of a class of multilayer perceptron
-
Roy, A., Kim, L., & Mukhopadhyay, S. (1993). A polynomial time algorithm for the construction and training of a class of multilayer perceptron. Neural Networks, 6(1), 535-545.
-
(1993)
Neural Networks
, vol.6
, Issue.1
, pp. 535-545
-
-
Roy, A.1
Kim, L.2
Mukhopadhyay, S.3
-
36
-
-
1542639878
-
Neural trees: A new tool for classification
-
Sirat, J. A., & Nadal, J.-P. (1990). Neural trees: A new tool for classification. Network, 1, 423-438.
-
(1990)
Network
, vol.1
, pp. 423-438
-
-
Sirat, J.A.1
Nadal, J.-P.2
-
37
-
-
0010266979
-
Learning and generalization in layered neural networks: The contiguity problem
-
L. Personnaz & G. Dreyfus (Eds.) Paris: I.D.S.E.T.
-
Solla, S. A. (1989). Learning and generalization in layered neural networks: The contiguity problem. In L. Personnaz & G. Dreyfus (Eds.), Neural Networks from Models to Applications. Paris: I.D.S.E.T.
-
(1989)
Neural Networks from Models to Applications
-
-
Solla, S.A.1
-
38
-
-
0012838621
-
An evolutive architecture coupled with optimal perceptron learning for classification
-
M. Verleysen (Ed.) Brussels: D Facto
-
Torres Moreno, J.-M., & Gordon, M. B. (1995). An evolutive architecture coupled with optimal perceptron learning for classification. In M. Verleysen (Ed.), European Symposium on Artificial Neural Networks. Brussels: D Facto.
-
(1995)
European Symposium on Artificial Neural Networks
-
-
Torres Moreno, J.-M.1
Gordon, M.B.2
-
39
-
-
0031992026
-
Characterization of the sonar signals benchmark
-
Torres Moreno, J.-M., & Gordon, M. B. (1998). Characterization of the sonar signals benchmark. Neural Proc. Letters, 7(1), 1-4.
-
(1998)
Neural Proc. Letters
, vol.7
, Issue.1
, pp. 1-4
-
-
Torres Moreno, J.-M.1
Gordon, M.B.2
-
41
-
-
0040864988
-
Principles of risk minimization for learning theory
-
J. E. Moody, S. J. Hanson, & R. P. Lippmann (Eds.) San Mateo, CA: Morgan Kaufmann
-
Vapnik, V. (1992). Principles of risk minimization for learning theory. In J. E. Moody, S. J. Hanson, & R. P. Lippmann (Eds.), Advances in neural information processing systems, 4 (pp. 831-838). San Mateo, CA: Morgan Kaufmann.
-
(1992)
Advances in Neural Information Processing Systems
, vol.4
, pp. 831-838
-
-
Vapnik, V.1
-
42
-
-
0346502480
-
A new algorithm for feedforward neural networks
-
M. Verleysen (Ed.) Brussels: D Facto
-
Verma, B. K., & Mulawka, J. J. (1995). A new algorithm for feedforward neural networks. In M. Verleysen (Ed.), European Symposium on Artificial Neural Networks (pp. 359-364). Brussels: D Facto.
-
(1995)
European Symposium on Artificial Neural Networks
, pp. 359-364
-
-
Verma, B.K.1
Mulawka, J.J.2
-
43
-
-
0025651706
-
Multisurface method of pattern separation for medical diagnosis applied to breast cytology
-
Wolberg, W. H., & Mangasarian, O. L. (1990). Multisurface method of pattern separation for medical diagnosis applied to breast cytology. In Proceedings of the National Academy of Sciences, USA, 87, 9193-9196.
-
(1990)
Proceedings of the National Academy of Sciences, USA
, vol.87
, pp. 9193-9196
-
-
Wolberg, W.H.1
Mangasarian, O.L.2
|