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Sparse LearningtoRank via an Efficient PrimalDual Algorithm
"... Abstract—Learningtorank for information retrieval has gained increasing interest in recent years. Inspired by the success of sparse models, we consider the problem of sparse learningtorank, where the learned ranking models are constrained to be with only a few nonzero coefficients. We begin by ..."
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Cited by 4 (0 self)
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from the primal dual perspective. Furthermore, we prove that, after at most O ( 1) iterations, the proposed algorithm can guarantee the obtainment of an ɛaccurate ɛ solution. This convergence rate is better than that of the popular subgradient descent algorithm. i.e., O ( 1 ɛ2). Empirical evaluation
A firstorder primaldual algorithm for convex problems with applications to imaging
, 2010
"... In this paper we study a firstorder primaldual algorithm for convex optimization problems with known saddlepoint structure. We prove convergence to a saddlepoint with rate O(1/N) in finite dimensions, which is optimal for the complete class of nonsmooth problems we are considering in this paper ..."
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Cited by 436 (20 self)
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In this paper we study a firstorder primaldual algorithm for convex optimization problems with known saddlepoint structure. We prove convergence to a saddlepoint with rate O(1/N) in finite dimensions, which is optimal for the complete class of nonsmooth problems we are considering
PrimalDual Combinatorial Algorithms
"... Linear program and its duality have long been ubiquitous tools for analyzing NPhard 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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wide range of problems including multicommodity flow. The key ideas there are: 1) design a primal oracle with partial constraints which can employ existing efficient combinatorial algorithms; 2) perform multiplicative updates on dual variables from the “feedback ” of the oracle and drive the solution
PDGA: the primaldual genetic algorithm
 Design and Application of Hybrid Intelligent Systems
, 2003
"... Abstract. Genetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the performance of GAs. In this paper inspired by the mechanisms of complementarity and dominance that broadly exist in nature, we ..."
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Cited by 5 (3 self)
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present a new genetic algorithm — PrimalDual Genetic Algorithm (PDGA). PDGA operates on a pair of chromosomes that are primaldual to each other through the primaldual mapping, which maps one to the other with a maximum distance away in a given distance space in genotype. The primaldual mapping
PrimalDual InteriorPoint Methods for SelfScaled Cones
 SIAM Journal on Optimization
, 1995
"... In this paper we continue the development of a theoretical foundation for efficient primaldual interiorpoint algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are selfscaled (see [9]). The class of problems under consideration includes li ..."
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Cited by 206 (12 self)
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In this paper we continue the development of a theoretical foundation for efficient primaldual interiorpoint algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are selfscaled (see [9]). The class of problems under consideration includes
Efficient Variants of the ICP Algorithm
 INTERNATIONAL CONFERENCE ON 3D DIGITAL IMAGING AND MODELING
, 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
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Cited by 718 (5 self)
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The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points
A Combinatorial, PrimalDual approach to Semidefinite Programs
"... Semidefinite programs (SDP) have been used in many recent approximation algorithms. We develop a general primaldual approach to solve SDPs using a generalization of the wellknown multiplicative weights update rule to symmetric matrices. For a number of problems, such as Sparsest Cut and Balanced ..."
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Cited by 94 (10 self)
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and Balanced Separator in undirected and directed weighted graphs, and the Min UnCut problem, this yields combinatorial approximation algorithms that are significantly more efficient than interior point methods. The design of our primaldual algorithms is guided by a robust analysis of rounding algorithms used
An Efficient ContextFree Parsing Algorithm
, 1970
"... A parsing algorithm which seems to be the most efficient general contextfree algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar topdown algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general; i ..."
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Cited by 798 (0 self)
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A parsing algorithm which seems to be the most efficient general contextfree algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar topdown algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general
An Efficient Boosting Algorithm for Combining Preferences
, 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
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Cited by 727 (18 self)
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The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new
Primaldual Strategy for Constrained Optimal Control Problems
, 1997
"... . An algorithm for efficient solution of control constrained optimal control problems is proposed and analyzed. It is based on an active set strategy involving primal as well as dual variables. For discretized problems sufficient conditions for convergence in finitely many iterations are given. Nume ..."
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Cited by 78 (6 self)
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. An algorithm for efficient solution of control constrained optimal control problems is proposed and analyzed. It is based on an active set strategy involving primal as well as dual variables. For discretized problems sufficient conditions for convergence in finitely many iterations are given
Results 1  10
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