Results 1 - 10 of 105,100

Sparse Learning-to-Rank via an Efficient Primal-Dual Algorithm

by Hanjiang Lai, Yan Pan, Cong Liu, Liang Lin, Jie Wu
"... Abstract—Learning-to-rank for information retrieval has gained increasing interest in recent years. Inspired by the success of sparse models, we consider the problem of sparse learning-to-rank, where the learned ranking models are constrained to be with only a few non-zero coefficients. We begin by ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
from the primal dual perspective. Furthermore, we prove that, after at most O ( 1) iterations, the proposed algorithm can guarantee the obtainment of an ɛ-accurate ɛ solution. This convergence rate is better than that of the popular sub-gradient descent algorithm. i.e., O ( 1 ɛ2). Empirical evaluation

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 436 (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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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 primal-dual genetic algorithm

by Shengxiang Yang - 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 ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
present a new genetic algorithm — Primal-Dual Genetic Algorithm (PDGA). PDGA operates on a pair of chromosomes that are primal-dual to each other through the primal-dual mapping, which maps one to the other with a maximum distance away in a given distance space in genotype. The primal-dual mapping

Primal-Dual Interior-Point Methods for Self-Scaled Cones

by Yu Nesterov, M. J. Todd - SIAM Journal on Optimization , 1995
"... In this paper we continue the development of a theoretical foundation for efficient primal-dual interior-point algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are self-scaled (see [9]). The class of problems under consideration includes li ..."
Abstract - Cited by 206 (12 self) - Add to MetaCart
In this paper we continue the development of a theoretical foundation for efficient primal-dual interior-point algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are self-scaled (see [9]). The class of problems under consideration includes

Efficient Variants of the ICP Algorithm

by Szymon Rusinkiewicz, Marc Levoy - INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING , 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional 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 ..."
Abstract - Cited by 718 (5 self) - Add to MetaCart
The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional 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, Primal-Dual approach to Semidefinite Programs

by Sanjeev Arora, et al.
"... Semidefinite programs (SDP) have been used in many recent approximation algorithms. We develop a general primal-dual approach to solve SDPs using a generalization of the well-known multiplicative weights update rule to symmetric matrices. For a number of problems, such as Sparsest Cut and Balanced ..."
Abstract - Cited by 94 (10 self) - Add to MetaCart
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 primal-dual algorithms is guided by a robust analysis of rounding algorithms used

An Efficient Context-Free Parsing Algorithm

by Jay Earley , 1970
"... A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general; i ..."
Abstract - Cited by 798 (0 self) - Add to MetaCart
A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down 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

by Raj Dharmarajan Iyer , Jr. , 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 ..."
Abstract - Cited by 727 (18 self) - Add to MetaCart
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

Primal-dual Strategy for Constrained Optimal Control Problems

by Maïtine Bergounioux, Kazufumi Ito, Karl Kunisch , 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 ..."
Abstract - Cited by 78 (6 self) - Add to MetaCart
. 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 of 105,100