Low-storage, second-order learning algorithms: an extended abstract
M.H. Schneider, K. Farrow, C. Neti · 1991
Summary form only given, as follows. Variants of Newton and quasi-Newton methods are discussed that require neither construction of matrices nor solution of systems of equations. These methods were applied to solve estimation problems arising in feedforward neural network models. Numerical results were obtained for sonar classification problems.>