Convex majorization methods for nonconvex constrained problems achieve O(ε^{-(κ+1)/κ}) iteration complexity under Hölderian gradients, with a second-order variant reaching approximate second-order stationarity in O(1/ε1+1/ε2) subproblem solves.
Nonlinear programming.Journal of the Operational Research Society, 48(3):334–334, 1997
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Complexity Analysis of Convex Majorization Schemes for Nonconvex Constrained Optimization
Convex majorization methods for nonconvex constrained problems achieve O(ε^{-(κ+1)/κ}) iteration complexity under Hölderian gradients, with a second-order variant reaching approximate second-order stationarity in O(1/ε1+1/ε2) subproblem solves.