Richard M. Golden

Biography

Dr. Richard Golden is a leading researcher in the field of the mathematical analysis and design of statistical machine learning algorithms with applications to modeling problems in the neural, behavioral, and social sciences. His research includes asymptotic behavior of stochastic adaptive nonlinear learning machines, statistical inference in the simultaneous presence of missing data and model misspecification, specification tests for detecting presence of model misspecification, and model selection in the presence of uncertainty. And, for over a decade, Dr. Golden served on the Editorial Boards of the Journal of Mathematical Psychology and Neural Networks. Dr. Golden earned his bachelor’s degree at the University of California at San Diego, and his master’s and doctoral degrees at Brown University.

Recent and Selected Representative Publications

Books

Statistical Machine Learning: A Unified Framework. Golden, R. M. (forthcoming 2020). CRC Press/Chapman-Hill. Boca Raton, Fl.

Mathematical Methods for Neural Network Analysis and Design. Golden, R. M. (1996). MIT Press, Cambridge, MA. [419 pages].

Recent Peer-Refereed Book Chapters and Journal Articles

Golden, R. M. (2018). Adaptive learning algorithm convergence in passive and reactive environments. Neural Computation, 30 (10), 2805-2832.

Golden, R. M., Henley, S.S., White, H., Kashner, T. M. (2016). Generalized information matrix tests for detecting model misspecification. Econometrics, 4.