Fast approximation algorithms for fractional packing and covering problems
Mathematics of Operations Research
Rounding of polytopes in the real number model of computation
Mathematics of Operations Research
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Smooth minimization of non-smooth functions
Mathematical Programming: Series A and B
Excessive Gap Technique in Nonsmooth Convex Minimization
SIAM Journal on Optimization
Unconstrained Convex Minimization in Relative Scale
Mathematics of Operations Research
Sparse non-Gaussian component analysis
IEEE Transactions on Information Theory
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In this paper, we propose new efficient gradient schemes for two non-trivial classes of linear programming problems. These schemes are designed to compute approximate solutions with relative accuracy δ. We prove that the upper complexity bound for both schemes is O((√(n ln m)/δ)ln n) iterations of a gradient-type method, where n and m (n