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math.OC2019
An accelerated first-order method with complexity analysis for solving cubic regularization subproblems
Rujun Jiang, Man-Chung Yue, Zhishuo Zhou
We propose a first-order method to solve the cubic regularization subproblem (CRS) based on a novel reformulation. The reformulation is a constrained convex optimization problem wh…
math.OC2019★ 4 cited
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue +2
A fundamental problem arising in many areas of machine learning is the evaluation of the likelihood of a given observation under different nominal distributions. Frequently, these…