Showing papers on "Empirical risk minimization published in 1972"

Research and Theory on the Learning of Probabilities

Abstract: Human behavior in many situations involving uncertainty and risk depends on the acquisition of information concerning event probabilities. A family of statistical models, growing out of general mathematical learning theory, accounts for probability learning in terms of the accumulation in memory of weighted ensembles of associations between recurring situations and subsequent events. These models provide rather detailed quantitative accounts of probability learning in some especially simplified experimental situations. Also they provide vehicles for applying theoretical interpretations of probability learning to the problems of choice and decision making in social and economic contexts.

Learning algorithms of pattern recognition in non-stationary conditions

Abstract: Publisher Summary This chapter discusses learning algorithms of pattern recognition in nonstationary conditions. The solution of the problems of learning in pattern recognition under stationary conditions lies in real, iterative algorithms, coinciding in their basis with stochastic approximation type algorithms. The general approach, permitting one to obtain various learning algorithms involves the development of the adaptive approach for learning under nonstationary conditions for learning under stationary conditions. At this stage, the question of recognition under nonstationary conditions is formulated and its solution is found at different stages of information, that is, at different stages of completeness of a priori information. This solution is obtained by considering learning algorithms on the basis of the general approach to learning under nonstationary conditions. The chapter presents a general method for establishing pattern recognition learning algorithms for both supervised and unsupervised learning under nonstationary conditions. The algorithms are learning systems that are capable, with time and after training, of accomplishing recognition of presented patterns.