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- Convex Optimization problem

by Jae Young Park, Anna C. Gilbert, Silvio Savarese
"... dog cat stapler ..."
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dog cat stapler

Approximating Parameterized Convex Optimization Problems ∗

by Joachim Giesen, Martin Jaggi , 2010
"... We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ε-approximate solution (and a corresponding ε-coreset) along the entire parameter path. We prove correctness and parameterized optim ..."
Abstract - Cited by 11 (3 self) - Add to MetaCart
We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ε-approximate solution (and a corresponding ε-coreset) along the entire parameter path. We prove correctness and parameterized

Residual selection model for convex optimization problems

by Robert Dylewski
"... We present residual selection method for convex optimization problems, in particular for convex feasibility problems. We show that the residual selection method is a special case of the surrogate constraints method. We also present ..."
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We present residual selection method for convex optimization problems, in particular for convex feasibility problems. We show that the residual selection method is a special case of the surrogate constraints method. We also present

Elementary Algorithms for Solving Convex Optimization Problems

by Negar Soheili Azad
"... The rapid growth in data availability has led to modern large scale convex optimization problems that pose new practical and theoretical challenges. Examples include classifica-tion problems such as customer segmentation in retail and credit scoring in insurance. Classical optimization and machine l ..."
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The rapid growth in data availability has led to modern large scale convex optimization problems that pose new practical and theoretical challenges. Examples include classifica-tion problems such as customer segmentation in retail and credit scoring in insurance. Classical optimization and machine

Convex Optimization Problems Involving Finite autocorrelation sequences

by Brien Alkire, Lieven Vandenberghe , 2001
"... We discuss convex optimization problems where some of the variables are constrained to be finite autocorrelation sequences. Problems of this form arise in signal processing and communications, and we describe applications in filter design and system identification. Autocorrelation constraints in opt ..."
Abstract - Cited by 40 (2 self) - Add to MetaCart
We discuss convex optimization problems where some of the variables are constrained to be finite autocorrelation sequences. Problems of this form arise in signal processing and communications, and we describe applications in filter design and system identification. Autocorrelation constraints

SEPARABLE CONVEX OPTIMIZATION PROBLEMS WITH LINEAR ASCENDING CONSTRAINTS

by Arun Padakandla, Rajesh Sundaresan - SUBMITTED TO THE SIAM JOURNAL ON OPTIMIZATION, JUL. 2007. , 2007
"... Separable convex optimization problems with linear ascending inequality and equality constraints are addressed in this paper. Under an ordering condition on the slopes of the functions at the origin, an algorithm that determines the optimum point in a finite number of steps is described. The optimu ..."
Abstract - Cited by 8 (4 self) - Add to MetaCart
Separable convex optimization problems with linear ascending inequality and equality constraints are addressed in this paper. Under an ordering condition on the slopes of the functions at the origin, an algorithm that determines the optimum point in a finite number of steps is described

On The Generic Properties Of Convex Optimization Problems In Conic Form

by Gábor Pataki, Levent Tunçel , 1997
"... We prove that strict complementarity, primal and dual nondegeneracy of optimal solutions of convex optimization problems in conic form are generic properties. In this paper, we say generic to mean that the set of data possessing the desired property (or properties) has the same Hausdorff measure as ..."
Abstract - Cited by 21 (3 self) - Add to MetaCart
We prove that strict complementarity, primal and dual nondegeneracy of optimal solutions of convex optimization problems in conic form are generic properties. In this paper, we say generic to mean that the set of data possessing the desired property (or properties) has the same Hausdorff measure

Global and uniform convergence of subspace correction methods for some convex optimization problems

by Jinchao Xu - Math. Comp , 2001
"... Abstract. This paper gives some global and uniform convergence estimates for a class of subspace correction (based on space decomposition) iterative methods applied to some unconstrained convex optimization problems. Some multigrid and domain decomposition methods are also discussed as special examp ..."
Abstract - Cited by 29 (10 self) - Add to MetaCart
Abstract. This paper gives some global and uniform convergence estimates for a class of subspace correction (based on space decomposition) iterative methods applied to some unconstrained convex optimization problems. Some multigrid and domain decomposition methods are also discussed as special

Sequential optimality conditions for composed convex optimization problems

by Radu Ioan Boţ , et al.
"... ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
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ε-optimality conditions for composed convex optimization problems

by Radu Ioan Boţ , et al.
"... ..."
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