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PROPOSED METHOD

by Iason Oikonomidis, Nikolaos Kyriazis, Antonis A. Argyros
"... full articulation (26 DoFs) of a human hand that possibly manipulates an object, given a sequence of either multiview or RGB-D frames of the scene. ..."
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full articulation (26 DoFs) of a human hand that possibly manipulates an object, given a sequence of either multiview or RGB-D frames of the scene.

Proposed Method

by M. Iwamura, T. Tsuji, A. Horimatsu, K. Kise, Real-time Camera-based Character
"... Recognizes all characters in a scene and provide useful information only Voice navigation for visually disabled people “Push button ” is on your right side Translation service for foreign travelers Car-free mall ..."
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Recognizes all characters in a scene and provide useful information only Voice navigation for visually disabled people “Push button ” is on your right side Translation service for foreign travelers Car-free mall

A Comparison of Methods for Multiclass Support Vector Machines

by Chih-Wei Hsu, Chih-Jen Lin - IEEE TRANS. NEURAL NETWORKS , 2002
"... Support vector machines (SVMs) were originally designed for binary classification. How to effectively extend it for multiclass classification is still an ongoing research issue. Several methods have been proposed where typically we construct a multiclass classifier by combining several binary class ..."
Abstract - Cited by 952 (22 self) - Add to MetaCart
Support vector machines (SVMs) were originally designed for binary classification. How to effectively extend it for multiclass classification is still an ongoing research issue. Several methods have been proposed where typically we construct a multiclass classifier by combining several binary

Large margin methods for structured and interdependent output variables

by Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract - Cited by 624 (12 self) - Add to MetaCart
that solves the optimization problem in polynomial time for a large class of problems. The proposed method has important applications in areas such as computational biology, natural language processing, information retrieval/extraction, and optical character recognition. Experiments from various domains

Interior-point Methods

by Florian A. Potra, Stephen J. Wright , 2000
"... The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for linear programming. In the years since then, algorithms and software for linear programming have become quite sophisticated, while extensions to more general classes of problems, such as convex quadrati ..."
Abstract - Cited by 612 (15 self) - Add to MetaCart
The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for linear programming. In the years since then, algorithms and software for linear programming have become quite sophisticated, while extensions to more general classes of problems, such as convex

Unified analysis of discontinuous Galerkin methods for elliptic problems

by Douglas N. Arnold, Franco Brezzi, Bernardo Cockburn, L. Donatella Marini - SIAM J. Numer. Anal , 2001
"... Abstract. We provide a framework for the analysis of a large class of discontinuous methods for second-order elliptic problems. It allows for the understanding and comparison of most of the discontinuous Galerkin methods that have been proposed over the past three decades for the numerical treatment ..."
Abstract - Cited by 525 (31 self) - Add to MetaCart
Abstract. We provide a framework for the analysis of a large class of discontinuous methods for second-order elliptic problems. It allows for the understanding and comparison of most of the discontinuous Galerkin methods that have been proposed over the past three decades for the numerical

On Sequential Monte Carlo Sampling Methods for Bayesian Filtering

by Arnaud Doucet, Simon Godsill, Christophe Andrieu - STATISTICS AND COMPUTING , 2000
"... In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is develop ..."
Abstract - Cited by 1051 (76 self) - Add to MetaCart
is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed. We show in particular how to incorporate local linearisation methods similar to those which have previously

General methods for monitoring convergence of iterative simulations

by Stephen P. Brooksand, Andrew Gelman - J. Comput. Graph. Statist , 1998
"... We generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence. We review methods of inference from simulations in order to develo ..."
Abstract - Cited by 551 (8 self) - Add to MetaCart
We generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence. We review methods of inference from simulations in order

Sequential Monte Carlo Methods for Dynamic Systems

by Jun S. Liu, Rong Chen - Journal of the American Statistical Association , 1998
"... A general framework for using Monte Carlo methods in dynamic systems is provided and its wide applications indicated. Under this framework, several currently available techniques are studied and generalized to accommodate more complex features. All of these methods are partial combinations of three ..."
Abstract - Cited by 664 (13 self) - Add to MetaCart
A general framework for using Monte Carlo methods in dynamic systems is provided and its wide applications indicated. Under this framework, several currently available techniques are studied and generalized to accommodate more complex features. All of these methods are partial combinations of three

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

by Jianqing Fan , Runze Li , 2001
"... Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized ..."
Abstract - Cited by 948 (62 self) - Add to MetaCart
likelihood approaches are proposed to handle these kinds of problems. The proposed methods select variables and estimate coefficients simultaneously. Hence they enable us to construct confidence intervals for estimated parameters. The proposed approaches are distinguished from others in that the penalty
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