-
1
-
-
0347963789
-
GTM: The generative topographic mapping
-
Bishop, C. M., Svensen, M., & Williams, C. K. I. (1998). GTM: The generative topographic mapping. Neural Computation, 10, 215-234.
-
(1998)
Neural Computation
, vol.10
, pp. 215-234
-
-
Bishop, C.M.1
Svensen, M.2
Williams, C.K.I.3
-
2
-
-
0002629270
-
Maximum likelihood from incomplete data via the EM algorithm
-
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc., Ser. B, 39, 1-38.
-
(1977)
J. Roy. Statist. Soc., Ser. B
, vol.39
, pp. 1-38
-
-
Dempster, A.P.1
Laird, N.M.2
Rubin, D.B.3
-
4
-
-
0004009232
-
-
(Tech. Rep. No. FIA-90-12-7-01). Moffet Field, CA: NASA Ames Research Center
-
Hanson, R., Stutz, J., & Cheeseman, P. (1991). Bayesian classification theory (Tech. Rep. No. FIA-90-12-7-01). Moffet Field, CA: NASA Ames Research Center.
-
(1991)
Bayesian Classification Theory
-
-
Hanson, R.1
Stutz, J.2
Cheeseman, P.3
-
6
-
-
0000262562
-
Hierarchical mixtures of experts and the EM algorithm
-
Jordan, M. I., & Jacobs, R. A. (1994). Hierarchical mixtures of experts and the EM algorithm. Neural Computation, 6, 181-214.
-
(1994)
Neural Computation
, vol.6
, pp. 181-214
-
-
Jordan, M.I.1
Jacobs, R.A.2
-
7
-
-
0029617280
-
Convergence results for the EM approach to mixtures of expert architectures
-
Jordan, M. I., & Xu, L. (1995). Convergence results for the EM approach to mixtures of expert architectures. Neural Networks, 8, 1409-1431.
-
(1995)
Neural Networks
, vol.8
, pp. 1409-1431
-
-
Jordan, M.I.1
Xu, L.2
-
9
-
-
0002704818
-
A practical Bayesian framework for backprop networks
-
MacKay, D. J. C. (1992). A practical Bayesian framework for backprop networks. Neural Computation, 4, 448-472.
-
(1992)
Neural Computation
, vol.4
, pp. 448-472
-
-
MacKay, D.J.C.1
-
11
-
-
85156248415
-
Improved gaussian mixture density estimates using Bayesian penalty terms and networks averaging
-
D. S. Touretzky, M. C. Mozer, M. E. Hasselmo (Eds.), Cambridge, MA: MIT Press
-
Ormoneit, D., & Tresp, V. (1996). Improved gaussian mixture density estimates using Bayesian penalty terms and networks averaging. In D. S. Touretzky, M. C. Mozer, M. E. Hasselmo (Eds.), Advances in neural information processing systems, 8 (pp. 542-548). Cambridge, MA: MIT Press.
-
(1996)
Advances in Neural Information Processing Systems
, vol.8
, pp. 542-548
-
-
Ormoneit, D.1
Tresp, V.2
-
12
-
-
0025490985
-
Networks for approximation and learning
-
Poggio, T., & Girosi, F. (1990). Networks for approximation and learning. Proc. IEEE, 78, 1481-1497.
-
(1990)
Proc. IEEE
, vol.78
, pp. 1481-1497
-
-
Poggio, T.1
Girosi, F.2
-
13
-
-
33846255123
-
Principal curves revisited
-
Tibshirani, R. (1992). Principal curves revisited. Statistics and Computing, 2, 183-190.
-
(1992)
Statistics and Computing
, vol.2
, pp. 183-190
-
-
Tibshirani, R.1
-
14
-
-
0004565770
-
Topology selection for self-organizing maps
-
Utsugi, A. (1996). Topology selection for self-organizing maps. Network, 7, 727-740.
-
(1996)
Network
, vol.7
, pp. 727-740
-
-
Utsugi, A.1
-
15
-
-
0005023590
-
Hyperparameter selection for self-organizing maps
-
Utsugi, A. (1997). Hyperparameter selection for self-organizing maps. Neural Computation, 9, 623-635.
-
(1997)
Neural Computation
, vol.9
, pp. 623-635
-
-
Utsugi, A.1
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