论文信息 - Mean field networks that learn to discriminate temporally distorted strings - 字舞流文

Mean field networks that learn to discriminate temporally distorted strings

Geoffrey E. Hinton | Christopher K. I. Williams

[1] Raymond L. Watrous,et al. Connected recognition with a recurrent network , 1990, Speech Commun..

[2] John S. Bridle,et al. Alpha-nets: A recurrent 'neural' network architecture with a hidden Markov model interpretation , 1990, Speech Commun..

[3] James L. McClelland,et al. Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.

[4] Geoffrey E. Hinton. Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space , 1989, Neural Computation.

[5] Raymond L. Watrous,et al. Complete gradient optimization of a recurrent network applied to /b/,/d/,/g/ discrimination , 1988 .

[6] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[7] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .

[8] Geoffrey E. Hinton,et al. A time-delay neural network architecture for isolated word recognition , 1990, Neural Networks.

[9] Carsten Peterson,et al. A Mean Field Theory Learning Algorithm for Neural Networks , 1987, Complex Syst..

[10] Geoffrey E. Hinton,et al. A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..