On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition

Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao

Abstract: We study constrained nonconvex optimization problems in machine learning and signal processing. It is well-known that these problems can be rewritten to a min-max problem in a Lagrangian form. Howe...