Selected Theoretical Statistical Machine Learning Publications
Golden,
Richard, M., Henley, S., White, H., and Kashner, T. M. (2013). New directions
in information matrix testing: Eigenspectrum tests. In Causality, Prediction, and Specification Analysis: Recent
Advances and Future Directions Essays in Honour of Halbert L. White Jr.
(Festschrift Hal White Conference), Norman Rasmus Swanson and Xiaohong Chen,
editors, New York: Spring, pp. 145-178.
Golden,
R. M. (2003). Discrepancy risk model selection test theory for comparing
possibily misspecified or nonnested models. Psychometrika,
68, 229-249.
Golden, R. M. (2000). Statistical tests for
comparing possibly misspecified and non-nested models. Journal of Mathematical Psychology.
Golden,
R. M. (1997). Optimal statistical goals for neural networks are necessary,
important, and practical. In D. S. Levine and W. R. Elsberry (eds.) Optimality
in Biological and Artificial Networks?
Mahwah: New Jersey. Erlbaum, 145-159.
Golden,
R. M. (1996). Mathematical Methods for Neural Network Analysis and Design. MIT
Press, Cambidge: MA.
Rumelhart,
D. E., Durbin, R., Golden, R. M., Chauvin, Y. (1996). Backpropagation: The
basic theory. In P. Smolensky, M. C.
Mozer, and D.E. Rumelhart (eds.) Mathematical
Perspectives on Neural Networks, Erlbaum:
NJ, 553-566.
Golden, R. M. (1995).
Making correct statistical inferences using a wrong probability model. Journal
of Mathematical Psychology, 39, 3-20.
Golden,
R. M. (1993). Stability and optimization analyses of the generalized
brain-state-in-a-box neural network model. Journal of Mathematical
Psychology, 37, 282-298.
Golden, R. M. (1988a).
Probabilistic characterization of neural model computations. In D. Z. Anderson
(Ed.) Neural Networks and Information Processing. New York, NY: AIP,
310-316.
Golden, R. M. (1988b). A
unified framework for connectionist systems. Biological Cybernetics, 59, 109-120.
Golden, R. M. (1986).
The "Brain-State-in-a-Box" neural model is a gradient descent
algorithm. Journal of Mathematical Psychology, 30, 73-80.