AbstractSemidefinite programs are convex optimization problems arising in a wide variety of applications and are the extension of linear programming. Most methods for linear programming have been generalized to semidefinite programs. Just as in linear programming, duality theorem plays a basic and an important role in theory as well as in algorithmics. Based on the discretization method and convergence property, this paper proposes a new proof of the strong duality theorem for semidefinite programming, which is different from other common proofs and is more simple
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
AbstractSemidefinite programs are convex optimization problems arising in a wide variety of applicat...
In this paper, an exact dual is derived for Semidefinite Programming (SDP), for which strong duality...
In this paper, an exact dual is derived for Semidefinite Programming (SDP), for which strong duality...
It is well known that the duality theory for linear programming (LP) is powerful and elegant and lie...
AbstractTwo dual problems are proposed for the minimax problem: minimize maxy ϵ Y φ(x, y), subject t...
AbstractSemi-definite programs are convex optimization problems arising in a wide variety of applica...
In semidefinite programming (SDP), unlike in linear programming, Farkas’ lemma may fail to prove inf...
In semidefinite programming (SDP), unlike in linear programming, Farkas’ lemma may fail to prove inf...
AbstractLinear semi-infinite programming deals with the optimization of linear functionals on finite...
In semidefinite programming one minimizes a linear function subject to the constraint that an affine...
International audienceWe introduce a new class of algorithms for solving linear semidefinite program...
Recently, semidefinite optimization problems have been intensively studied since many optimization p...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
AbstractSemidefinite programs are convex optimization problems arising in a wide variety of applicat...
In this paper, an exact dual is derived for Semidefinite Programming (SDP), for which strong duality...
In this paper, an exact dual is derived for Semidefinite Programming (SDP), for which strong duality...
It is well known that the duality theory for linear programming (LP) is powerful and elegant and lie...
AbstractTwo dual problems are proposed for the minimax problem: minimize maxy ϵ Y φ(x, y), subject t...
AbstractSemi-definite programs are convex optimization problems arising in a wide variety of applica...
In semidefinite programming (SDP), unlike in linear programming, Farkas’ lemma may fail to prove inf...
In semidefinite programming (SDP), unlike in linear programming, Farkas’ lemma may fail to prove inf...
AbstractLinear semi-infinite programming deals with the optimization of linear functionals on finite...
In semidefinite programming one minimizes a linear function subject to the constraint that an affine...
International audienceWe introduce a new class of algorithms for solving linear semidefinite program...
Recently, semidefinite optimization problems have been intensively studied since many optimization p...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...
The semidefinite programming is an optimization approach where optimization problems are formulated ...