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Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently

Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently

Yaodong Yu
Difan Zou
Quanquan Gu
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Papers citing "Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently"

3 / 3 papers shown
Title
Sub-sampled Cubic Regularization for Non-convex Optimization
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Köhler
Aurelien Lucchi
31
165
0
16 May 2017
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park
Anastasios Kyrillidis
Constantine Caramanis
Sujay Sanghavi
35
180
0
12 Sep 2016
Matrix Completion has No Spurious Local Minimum
Matrix Completion has No Spurious Local Minimum
Rong Ge
Jason D. Lee
Tengyu Ma
41
597
0
24 May 2016

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