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Particle swarm optimization

by James Kennedy, Russell Eberhart , 1995
"... eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications ..."
Abstract - Cited by 3535 (22 self) - Add to MetaCart
eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described

Bundle Adjustment -- A Modern Synthesis

by Bill Triggs, Philip McLauchlan, Richard Hartley, Andrew Fitzgibbon - VISION ALGORITHMS: THEORY AND PRACTICE, LNCS , 2000
"... This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics c ..."
Abstract - Cited by 555 (12 self) - Add to MetaCart
This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics

Support-Vector Networks

by Corinna Cortes, Vladimir Vapnik - Machine Learning , 1995
"... The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special pr ..."
Abstract - Cited by 3621 (35 self) - Add to MetaCart
The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special

New results in linear filtering and prediction theory

by R. E. Kalman, R. S. Bucy - Trans. ASME, Ser. D, J. Basic Eng , 1961
"... A nonlinear differential equation of the Riccati type is derived for the covariance matrix of the optimal filtering error. The solution of this "variance equation " completely specifies the optimal filter for either finite or infinite smoothing intervals and stationary or nonstationary sta ..."
Abstract - Cited by 585 (0 self) - Add to MetaCart
A nonlinear differential equation of the Riccati type is derived for the covariance matrix of the optimal filtering error. The solution of this "variance equation " completely specifies the optimal filter for either finite or infinite smoothing intervals and stationary or nonstationary

An analysis of the principal-agent problem

by J. Grossman, Oliver D. Hart - ECONOMETRICA , 1983
"... ..."
Abstract - Cited by 451 (2 self) - Add to MetaCart
Abstract not found

Learning realistic human actions from movies

by Ivan Laptev, Marcin Marszałek, Cordelia Schmid, Benjamin Rozenfeld - IN: CVPR. , 2008
"... The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in the past due to several problems one of which is the lack of realistic and annotated video datasets. Our first contribut ..."
Abstract - Cited by 714 (51 self) - Add to MetaCart
next turn to the problem of action classification in video. We present a new method for video classification that builds upon and extends several recent ideas including local space-time features, space-time pyramids and multichannel non-linear SVMs. The method is shown to improve state

Randomized kinodynamic planning

by Steven M. Lavalle, James J. Kuffner, Jr. - THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378 , 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
Abstract - Cited by 620 (36 self) - Add to MetaCart
dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state

Inverse Acoustic and Electromagnetic Scattering Theory, Second Edition

by David Colton , 1998
"... Abstract. This paper is a survey of the inverse scattering problem for time-harmonic acoustic and electromagnetic waves at fixed frequency. We begin by a discussion of “weak scattering ” and Newton-type methods for solving the inverse scattering problem for acoustic waves, including a brief discussi ..."
Abstract - Cited by 1072 (45 self) - Add to MetaCart
Abstract. This paper is a survey of the inverse scattering problem for time-harmonic acoustic and electromagnetic waves at fixed frequency. We begin by a discussion of “weak scattering ” and Newton-type methods for solving the inverse scattering problem for acoustic waves, including a brief

A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II

by Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, T. Meyarivan , 2000
"... Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(MN computational complexity (where M is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing param ..."
Abstract - Cited by 1707 (58 self) - Add to MetaCart
to solve constrained multi-objective problems eciently. Simulation results of the constrained NSGA-II on a number of test problems, including a five-objective, seven-constraint non-linear problem, are compared with another constrained multi-objective optimizer and much better performance of NSGA

Convex Analysis

by R. Tyrrell Rockafellar , 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
Abstract - Cited by 5350 (67 self) - Add to MetaCart
In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a
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