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math.OC2023★ 2 cited
Riemannian stochastic optimization methods avoid strict saddle points
Ya-Ping Hsieh, Mohammad Reza Karimi, Andreas Krause +1
Many modern machine learning applications - from online principal component analysis to covariance matrix identification and dictionary learning - can be formulated as minimization…
math.OC2022
Riemannian stochastic approximation algorithms
Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos +1
We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of…