Motivated by applications arising from large scale optimization and machine learning, we consider stochastic quasiNewton (SQN) methods for solving unconstrained convex optimization problems. The convergence analysis of the SQN methods, both full and limitedmemory variants, require the objective function to be strongly convex... (read more)
PDFMETHOD  TYPE  

Logistic Regression

Generalized Linear Models 