Quadratic Programming
A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems
... l ≤ Ax ≤ ¯ h divided two part, ¯ l ≤ Ax and Ax ≤ ¯ h, thus dimension of problem increases. First time, Xia et al. studied [22] a neural network for solving (1.1) without dividing ¯ l ≤ Ax ≤ ¯ h into two part. Proposed ...
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An accelerating algorithm for globally solving nonconvex quadratic programming
... nonconvex quadratic programs; two efficient algorithms for linear constrained quadratic programming (LCQP) by Cam- bini et ...convex quadratic program with convex quadratic constraints ...
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Hedging Greeks for a portfolio of options using linear and quadratic programming
... A quadratic programming solution (which is NP-hard to solve) is formulated and then approximated to a linear programming ...linear programming solution has been developed in MS Excel using ...
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Learn to Solve Algebra Word Problems Using Quadratic Programming
... Results: Table 2 lists the learning statistics for our algorithm and (Kushman et al., 2014). We can ob- serve that the number of possible alignments per word problem of our algorithm is much smaller than (Kushman et al., ...
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Decomposition of mutational context signatures using quadratic programming methods
... the decomposition of a single sample, but rather than decomposing mutational contexts into signatures by fitting iterative linear mod- els (ILM), we have viewed the question as lying within the frame- work of ...
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Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem
... We study the Bipartite Boolean Quadratic Programming Problem (BBQP) which is an extension of the well known Boolean Quadratic Programming Problem (BQP). Applications of the BBQP include mining ...
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Conic Reformulation of Some Quadratic Programming Problems with Applications.
... non-convex quadratic programming programs with mixed binary and continuous variables as linear conic programming problem over the cone of completely positive matrices and proved the ...
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A comparison of quadratic programming solvers in support vector machines training
... tools to train the SVM. Vapnik [3] used a simple constrained conjugate gradient algorithm and an algorithm for bounded large-scale QP. In [4] the performances (in terms of training time) of four different optimizers are ...
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A Solution Approach for Solving Fully Fuzzy Quadratic Programming Problems
... These are pairs of one-level mathematical programs that clearly express the bounds of the objective values at a specific 𝛼 value. In these conventional quadratic programming problems, the objective ...
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Some Properties of Interval Quadratic Programming Problem
... interval quadratic programming ...linear programming) have been established in [4, ...interval quadratic programming problem have been ...interval quadratic program are ...
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Minimizing Complementary Pivots in a Simplex Based Solution Method for a Quadratic Programming Problem
... of quadratic programming: Quadratic programming has been successfully applied in areas such as engineering, finance, economics, agriculture, market- ing, public policy, water resource ...
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Conic Reformulations and Approximations to Some Subclasses of Nonconvex Quadratic Programming Problems.
... binary quadratic problem [34], the fractional quadratic problem [92], determining the clique number of a graph [81], graph partitioning [90] and the quadratic assignment problem [91], have been shown ...
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A New Numerical Method for Solving the Stokes Problem Using Quadratic Programming
... In this paper we transformed the Stokes problem into a quadratic programming problem, and by solving it, we obtained the velocity and pressure as a linear combina- tion of independent functions. The ...
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A Computationally Efficient Algorithm for Solving Fuzzy Quadratic Programming Problems
... also, quadratic programming problem (QPP) with fuzzy parameters has been ...fuzzy quadratic programming problem (FQPP) with fuzzy parameters into a pair of conventional mathematical programs ...
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Noisy Sparse Recovery Based on Parameterized Quadratic Programming by Thresholding
... parameterized quadratic programming (Lasso [9, 10], also called basis pursuit [11]) to deal with the noisy sparse recovery problem through minimizing the following objective function which simultaneously ...
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Quadratic Programming Feature Selection
... uses quadratic programming, a methodology that has previously been successful for a broad range of other quite different applications (Bertsekas, ...A quadratic programming problem is to ...
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Quadratic Programming with Discrete Variables.
... conic programming (LCoP) problem minimizes a linear function over the inter- section of an affine subspace and a convex cone, which may involve special structures such that the LCoP problem can be solved in ...
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Quadratic programming and penalized regression
... sion of the lasso estimator (Tibshirani, 1996) and it hence leads to sparse estimates. When approaching new data it is possible that the underlying signal function has a very simple form; sparse estimates can more easily ...
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Study on Fuzzy Quadratic Programming Problems
... fuzzy programming have been yielded[2,3,4,5,6] ...fuzzy programming, whose objective functions are fuzzy quadratic and constraint conditions are fuzzy linear, are called fuzzy quadratic ...
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A Quadratic Programming with Triangular Fuzzy Numbers
... Quadratic Programming (QP) is a mathematical modeling technique de- signed to optimize the usage of limited resources and has been widely applied to solve real world ...conventional quadratic ...
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