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A Homogeneous Interiorpoint Algorithm for . . .
"... A homogeneous infeasiblestart interiorpoint algorithm for solving nonsymmetric convex conic optimization problems is presented. Starting each iteration from the vicinity of the central path, the method steps in the approximate tangent direction and then applies a correction phase to locate the ne ..."
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A homogeneous infeasiblestart interiorpoint algorithm for solving nonsymmetric convex conic optimization problems is presented. Starting each iteration from the vicinity of the central path, the method steps in the approximate tangent direction and then applies a correction phase to locate
Interior Point Algorithms for Integer Programming
, 1994
"... Research on using interior point algorithms to solve integer programming problems is surveyed. This paper concentrates on branch and bound and cutting plane methods; a potential function method is also briefly mentioned. The principal difficulty with using an interior point algorithm in a branch and ..."
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Cited by 6 (4 self)
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Research on using interior point algorithms to solve integer programming problems is surveyed. This paper concentrates on branch and bound and cutting plane methods; a potential function method is also briefly mentioned. The principal difficulty with using an interior point algorithm in a branch
An InteriorPoint Algorithm For Nonconvex Nonlinear Programming
 COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
, 1997
"... The paper describes an interiorpoint algorithm for nonconvex nonlinear programming which is a direct extension of interiorpoint methods for linear and quadratic programming. Major modifications include a merit function and an altered search direction to ensure that a descent direction for the mer ..."
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Cited by 199 (14 self)
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The paper describes an interiorpoint algorithm for nonconvex nonlinear programming which is a direct extension of interiorpoint methods for linear and quadratic programming. Major modifications include a merit function and an altered search direction to ensure that a descent direction
Interiorpoint algorithms for linearprogramming decoding
, 2008
"... Interiorpoint algorithms constitute a very interesting class of algorithms for solving linearprogramming problems. In this paper we study efficient implementations of such algorithms for solving the linear program that appears in the linearprogramming decoder formulation. ..."
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Cited by 9 (0 self)
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Interiorpoint algorithms constitute a very interesting class of algorithms for solving linearprogramming problems. In this paper we study efficient implementations of such algorithms for solving the linear program that appears in the linearprogramming decoder formulation.
Interior Point Algorithms
, 1997
"... Stochastic Gradient Boosted Decision Trees (GBDT) is one of the most widely used learning algorithms in machine learning today. It is adaptable, easy to interpret, and produces highly accurate models. However, most implementations today are computationally expensive and require all training data t ..."
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Cited by 16 (0 self)
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Stochastic Gradient Boosted Decision Trees (GBDT) is one of the most widely used learning algorithms in machine learning today. It is adaptable, easy to interpret, and produces highly accurate models. However, most implementations today are computationally expensive and require all training data
On Some InteriorPoint Algorithms for Nonconvex Quadratic Optimization
 Math. Program
, 2000
"... Recently, interiorpoint algorithms have been applied to nonlinear and nonconvex optimization. Most of these algorithms are either primaldual pathfollowing or anescaling in nature, and some of them are conjectured to converge to a local minimum. We give several examples to show that this may be un ..."
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Cited by 3 (1 self)
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Recently, interiorpoint algorithms have been applied to nonlinear and nonconvex optimization. Most of these algorithms are either primaldual pathfollowing or anescaling in nature, and some of them are conjectured to converge to a local minimum. We give several examples to show that this may
Smoothed Analysis of InteriorPoint Algorithms: Termination
, 2003
"... We perform a smoothed analysis of the termination phase of an interiorpoint method. By combining this analysis with the smoothed analysis of Renegar’s interiorpoint algorithm in [DST02], we show that the smoothed complexity of an interiorpoint algorithm for linear programming is O(m 3 log(m/σ)). ..."
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Cited by 3 (1 self)
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We perform a smoothed analysis of the termination phase of an interiorpoint method. By combining this analysis with the smoothed analysis of Renegar’s interiorpoint algorithm in [DST02], we show that the smoothed complexity of an interiorpoint algorithm for linear programming is O(m 3 log
PRIMALDUAL INTERIORPOINT ALGORITHMS:
"... INTRODUCTION Spring 1995 We consider linear programming problems in the following primal (P ) and dual (D) forms: (P ) maximize c T x Ax = b; x 0; (D) minimize b T y A T y \Gamma s = c; s 0; where A 2 IR m\Thetan , b 2 IR m , and c 2 IR n (all vectors are column vectors). Note that w ..."
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that we have explicitly included the slack variables s. We will assume rank(A) = m (if not, we can do Gaussian elimination). For now, we will also assume that there exist interior solutions for both problems, i.e. there exist ¯<F
Results 1  10
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136,519