Semidefinite and Cone Programming Bibliography/Comments
نویسنده
چکیده
This paper presents abstracts (short outlines) of recent papers related to semidefinite programming. The papers are grouped by subject. Many of my own papers deal with SDP but may not included here yet. They are available at http://orion.math.uwaterloo.ca:80/ ̃hwolkowi/henry/reports/ABSTRACTS.html
منابع مشابه
Semidefinite and Second Order Cone Programming
1 Overview We survey the basic notions of cones and cone-LP and give several examples mostly related to semidefinite programming. The linear and semidefinite programming problems are formulated as follows: Let c ∈ n and b ∈ m ,A ∈ n×m with rows a i ∈
متن کاملA Recurrent Neural Network Model for Solving Linear Semidefinite Programming
In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...
متن کاملEla Semidefinite Geometry of the Numerical Range
Abstract. The numerical range of a matrix is studied geometrically via the cone of positive semidefinite matrices (or semidefinite cone for short). In particular, it is shown that the feasible set of a two-dimensional linear matrix inequality (LMI), an affine section of the semidefinite cone, is always dual to the numerical range of a matrix, which is therefore an affine projection of the semid...
متن کاملSemidefinite geometry of the numerical range
The numerical range of a matrix is studied geometrically via the cone of positive semidefinite matrices (or semidefinite cone for short). In particular it is shown that the feasible set of a two-dimensional linear matrix inequality (LMI), an affine section of the semidefinite cone, is always dual to the numerical range of a matrix, which is therefore an affine projection of the semidefinite con...
متن کاملSecond Order Cone Programming Relaxation of Nonconvex Quadratic Optimization Problems
A disadvantage of the SDP (semidefinite programming) relaxation method for quadratic and/or combinatorial optimization problems lies in its expensive computational cost. This paper proposes a SOCP (second-order-cone programming) relaxation method, which strengthens the lift-and-project LP (linear programming) relaxation method by adding convex quadratic valid inequalities for the positive semid...
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تاریخ انتشار 2001