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.