Results 1 - 10 of 1,473,651

A first-order primal-dual algorithm for convex problems with applications to imaging

by Antonin Chambolle, Thomas Pock , 2010
"... In this paper we study a first-order primal-dual algorithm for convex optimization problems with known saddle-point structure. We prove convergence to a saddle-point with rate O(1/N) in finite dimensions, which is optimal for the complete class of non-smooth problems we are considering in this paper ..."
Abstract - Cited by 435 (20 self) - Add to MetaCart
In this paper we study a first-order primal-dual algorithm for convex optimization problems with known saddle-point structure. We prove convergence to a saddle-point with rate O(1/N) in finite dimensions, which is optimal for the complete class of non-smooth problems we are considering

Primal-Dual Combinatorial Algorithms

by Qihui Zhu
"... Linear program and its duality have long been ubiquitous tools for analyzing NP-hard problems and designing fast approximation algorithms. Plotkin et al proposed a primaldual combinatorial algorithm based on linear duality for fractional packing and covering, which achieves significant speedup on a ..."
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to optimal. Recently, this algorithm is extended to SDP based relaxation on max-cut, sparsest cut (Arora et al), and general convex programming (Khandekar et al). In this paper, we summarize previous primal-dual algorithms as a unified computational paradigm. We show how several important applications can

primal-dual

by Minghui Zhu
"... Lagrangian ..."
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Lagrangian

PRIMAL-DUAL KERNEL MACHINES

by Prof G. De Roeck, Prof J. Suykens, Prof B. De Moor, Prof J. Vandewalle, Prof J. Schoukens (vub, Prof M. Hubert, Kristiaan Pelckmans , 2005
"... Proefschrift voorgedragen tot het behalen van het doctoraat in de ingenieurswetenschappen door ..."
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Proefschrift voorgedragen tot het behalen van het doctoraat in de ingenieurswetenschappen door

Sparsity Exploitation in Primal-Dual . . .

by Kazuhiro Kobayashi , 2008
"... ..."
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Abstract not found

Primal-Dual Path-Following Algorithms for Semidefinite Programming

by Renato D.C. Monteiro - SIAM Journal on Optimization , 1996
"... This paper deals with a class of primal-dual interior-point algorithms for semidefinite programming (SDP) which was recently introduced by Kojima, Shindoh and Hara [11]. These authors proposed a family of primal-dual search directions that generalizes the one used in algorithms for linear programmin ..."
Abstract - Cited by 169 (12 self) - Add to MetaCart
This paper deals with a class of primal-dual interior-point algorithms for semidefinite programming (SDP) which was recently introduced by Kojima, Shindoh and Hara [11]. These authors proposed a family of primal-dual search directions that generalizes the one used in algorithms for linear

A PRIMAL-DUAL AUGMENTED LAGRANGIAN

by Philip E. Gill, et al. , 2008
"... Nonlinearly constrained optimization problems can be solved by minimizing a sequence of simpler unconstrained or linearly constrained subproblems. In this paper, we discuss the formulation of subproblems in which the objective is a primal-dual generalization of the Hestenes-Powell augmented Lagrangi ..."
Abstract - Cited by 16 (2 self) - Add to MetaCart
Nonlinearly constrained optimization problems can be solved by minimizing a sequence of simpler unconstrained or linearly constrained subproblems. In this paper, we discuss the formulation of subproblems in which the objective is a primal-dual generalization of the Hestenes-Powell augmented

A Framework for Defining Logics

by Robert Harper , Furio Honsell, Gordon Plotkin - JOURNAL OF THE ASSOCIATION FOR COMPUTING MACHINERY , 1993
"... The Edinburgh Logical Framework (LF) provides a means to define (or present) logics. It is based on a general treatment of syntax, rules, and proofs by means of a typed -calculus with dependent types. Syntax is treated in a style similar to, but more general than, Martin-Lof's system of ariti ..."
Abstract - Cited by 807 (45 self) - Add to MetaCart
The Edinburgh Logical Framework (LF) provides a means to define (or present) logics. It is based on a general treatment of syntax, rules, and proofs by means of a typed -calculus with dependent types. Syntax is treated in a style similar to, but more general than, Martin-Lof's system

Maximizing Queueing Network Utility Subject to Stability: Greedy Primal-dual algorithm

by Alexander L. Stolyar - Queueing Systems , 2005
"... We study a model of controlled queueing network, which operates and makes control decisions in discrete time. An underlying random network mode determines the set of available controls in each time slot. Each control decision \produces " a certain vector of \commodities"; it also has assoc ..."
Abstract - Cited by 206 (9 self) - Add to MetaCart
is the average value of commodity vector, subject to the constraint that network queues remain stable. We introduce a dynamic control algorithm, which we call Greedy Primal-Dual (GPD) algorithm, and prove its asymptotic optimality. We show that our network model and GPD algorithm accommodate a wide range

Primal-Dual Monotone Kernel Regression

by K. Pelckmans, M. Espinoza, J. De Brabanter, J. A. K. Suykens, B. De Moor , 2004
"... This paper considers the estimation of monotone nonlinear regression based on Support Vector Machines (SVMs), Least Squares SVMs (LS-SVMs) and kernel machines. It illustrates how to employ the primal-dual optimization framework characterizing (LS-)SVMs in order to derive a globally optimal one-stage ..."
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This paper considers the estimation of monotone nonlinear regression based on Support Vector Machines (SVMs), Least Squares SVMs (LS-SVMs) and kernel machines. It illustrates how to employ the primal-dual optimization framework characterizing (LS-)SVMs in order to derive a globally optimal one
Results 1 - 10 of 1,473,651