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Results: 1-8 |
Results: 8
Learning distributed representations of concepts using linear relational embedding
Authors: Paccanaro, A Hinton, GE
Citation: A. Paccanaro et Ge. Hinton, Learning distributed representations of concepts using linear relational embedding, IEEE KNOWL, 13(2), 2001, pp. 232-244
Split and merge EM algorithm for improving Gaussian ixture density estimates
Authors: Ueda, N Nakano, R Ghahramani, Z Hinton, GE
Citation: N. Ueda et al., Split and merge EM algorithm for improving Gaussian ixture density estimates, J VLSI S P, 26(1-2), 2000, pp. 133-140
SMEM algorithm for mixture models
Authors: Ueda, N Nakano, R Ghahramani, Z Hinton, GE
Citation: N. Ueda et al., SMEM algorithm for mixture models, NEURAL COMP, 12(9), 2000, pp. 2109-2128
Variational learning for switching state-space models
Authors: Ghahramani, Z Hinton, GE
Citation: Z. Ghahramani et Ge. Hinton, Variational learning for switching state-space models, NEURAL COMP, 12(4), 2000, pp. 831-864
Variational learning in nonlinear Gaussian belief networks
Authors: Frey, BJ Hinton, GE
Citation: Bj. Frey et Ge. Hinton, Variational learning in nonlinear Gaussian belief networks, NEURAL COMP, 11(1), 1999, pp. 193-213
Learning mixture models of spatial coherence
Authors: Becker, S Hinton, GE
Citation: S. Becker et Ge. Hinton, Learning mixture models of spatial coherence, COMPUT NEUR, 1999, pp. 223-233
Learning population codes by minimizing description length
Authors: Zemel, RS Hinton, GE
Citation: Rs. Zemel et Ge. Hinton, Learning population codes by minimizing description length, COMPUT NEUR, 1999, pp. 261-276
The Helmholtz machine
Authors: Dayan, P Hinton, GE Neal, RM Zemel, RS
Citation: P. Dayan et al., The Helmholtz machine, COMPUT NEUR, 1999, pp. 277-292
Risultati: 1-8 |