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An augmented Lagrangian method for non-Lipschitz nonconvex programming
Xiaojun Chen
, Lei Guo
, Zhaosong Lu
, Jane J. Ye
Department of Applied Mathematics
The Hong Kong Polytechnic University
Research output
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Journal article publication
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Journal article
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Academic research
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peer-review
46
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Citations (Scopus)
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Keyphrases
Augmented Lagrangian Method
100%
Non-Lipschitz
100%
Nonconvex Programming
100%
Interior Point Method
75%
Accumulation Points
50%
Linear Dependence
50%
Sparse Portfolio Selection
50%
Numerical Results
25%
Signal Processing
25%
Numerical Experiments
25%
Constraint Function
25%
Nonconvex
25%
Constrained Optimization Problem
25%
Smooth Function
25%
Karush-Kuhn-Tucker
25%
Karush-Kuhn-Tucker Points
25%
Image Reconstruction
25%
Original Problem
25%
Portfolio Optimization
25%
Mangasarian-Fromovitz Constraint Qualification
25%
Dependence Conditions
25%
Affine
25%
Constraint Qualification
25%
Solution Quality
25%
Non-monotone
25%
Image Signal
25%
Stationary Conditions
25%
Proximal Gradient Method
25%
Edge Preserving
25%
Non-Lipschitz Function
25%
Mathematics
Lagrangian
100%
Interior Point
75%
Positive Constant
50%
Accumulation Point
50%
Linear Dependence
50%
Feasible Point
50%
Optimality
25%
Objective Function
25%
Smooth Function
25%
Lipschitz Function
25%
Edge
25%
Numerical Experiment
25%
Constrained Optimization Problem
25%
Constraint Function
25%
Stationary Condition
25%
Subproblem
25%
Signal Processing
25%