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SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
large-scale optimization nonlinear programming
2015/7/3
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective
and constraints.Here w...
LARGE-SCALE LINEARLY CONSTRAINED OPTIMIZATION
Large-scale Systems Linear Constraints Linear Programming
2015/7/3
An algorithm for solving large-scale nonlinear' programs with linear constraints is presented.
The method combines efficient sparse-matrix techniques as in the revised simplex method
with stable q...
Matrix completion via max-norm constrained optimization
Compressed sensing low-rank matrix matrix completion max-norm con-strained minimization optimal rate of convergence sparsity
2013/4/28
This paper studies matrix completion under a general sampling model using the max-norm as a convex relaxation for the rank of the matrix. The optimal rate of convergence is established for the Frobeni...
Feature Extraction for Universal Hypothesis Testing via Rank-constrained Optimization
Universal test mismatched universal test hypothesistesting feature extraction exponential family
2010/3/9
This paper concerns the construction of universal
tests for binary hypothesis testing, in which the alternate hypothesis
is poorly modeled and the observation space is large.
The mismatched univers...