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math.OC2022
Stochastic Variance Reduced Gradient for affine rank minimization problem
Ningning Han, Juan Nie, Jian Lu +1
We develop an efficient stochastic variance reduced gradient descent algorithm to solve the affine rank minimization problem consists of finding a matrix of minimum rank from linea…
math.OC2022
A Momentum Accelerated Adaptive Cubic Regularization Method for Nonconvex Optimization
Yihang Gao, Michael K. Ng
The cubic regularization method (CR) and its adaptive version (ARC) are popular Newton-type methods in solving unconstrained non-convex optimization problems, due to its global con…
math.OC2022
Approximate Secular Equations for the Cubic Regularization Subproblem
Yihang Gao, Man-Chung Yue, Michael K. Ng
The cubic regularization method (CR) is a popular algorithm for unconstrained non-convex optimization. At each iteration, CR solves a cubically regularized quadratic problem, calle…