Results 1  10
of
84
Direct least Square Fitting of Ellipses
, 1998
"... This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac  b² = 1 the new method incorporates the ellipticity constraint ..."
Abstract

Cited by 265 (3 self)
 Add to MetaCart
This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac  b² = 1 the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: (i) It is ellipsespecific so that even bad data will always return an ellipse; (ii) It can be solved naturally by a generalized eigensystem and (iii) it is extremely robust, efficient and easy to implement.
A comparison of classifiers and document representations for the routing problem
 ANNUAL ACM CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL  ACM SIGIR
, 1995
"... In this paper, we compare learning techniques based on statistical classification to traditional methods of relevance feedback for the document routing problem. We consider three classification techniques which have decision rules that are derived via explicit error minimization: linear discriminant ..."
Abstract

Cited by 164 (2 self)
 Add to MetaCart
In this paper, we compare learning techniques based on statistical classification to traditional methods of relevance feedback for the document routing problem. We consider three classification techniques which have decision rules that are derived via explicit error minimization: linear discriminant analysis, logistic regression, and neural networks. We demonstrate that the classifiers perform 1015 % better than relevance feedback via Rocchio expansion for the TREC2 and TREC3 routing tasks.
Error minimization is difficult in highdimensional feature spaces because the convergence process is slow and the models are prone to overfitting. We use two different strategies, latent semantic indexing and optimal term selection, to reduce the number of features. Our results indicate that features based on latent semantic indexing are more effective for techniques such as linear discriminant analysis and logistic regression, which have no way to protect against overfitting. Neural networks perform equally well with either set of features and can take advantage of the additional information available when both feature sets are used as input.
Dimensions of Meaning
, 1992
"... The representation of documents and queries as vectors in a highdimensional space is wellestablished in information retrieval [1]. This paper proposes to represent the semantics of words and contexts in a text as vectors. The dimensions of the space are words and the initial vectors are determined ..."
Abstract

Cited by 143 (5 self)
 Add to MetaCart
The representation of documents and queries as vectors in a highdimensional space is wellestablished in information retrieval [1]. This paper proposes to represent the semantics of words and contexts in a text as vectors. The dimensions of the space are words and the initial vectors are determined by the words occurring close to the entity to be represented which implies that the space has several thousand dimensions (words). This makes the vector representations (which are dense) too cumbersome to use directly. Therefore, dimensionality reduction by means of a singular value decomposition is employed. The paper analyzes the structure of the vector representations and applies them to word sense disambiguation and thesaurus induction.
Direct LeastSquares Fitting of Algebraic Surfaces
, 1987
"... In the course of developing a system for fitting smooth curves to camera input we have developed several direct (i.e. noniterative) methods for fitting a shape (line, circle, conic, cubic, plane, sphere, quadric, etc.) to a set of points, namely exact fit, simple fit, spherical fit, and blend fit. T ..."
Abstract

Cited by 112 (1 self)
 Add to MetaCart
In the course of developing a system for fitting smooth curves to camera input we have developed several direct (i.e. noniterative) methods for fitting a shape (line, circle, conic, cubic, plane, sphere, quadric, etc.) to a set of points, namely exact fit, simple fit, spherical fit, and blend fit. These methods are all dimensionindependent, being just as suitable for 3D surfaces as for the 2D curves they were originally developed for. Exact fit...
Split Selection Methods for Classification Trees
 STATISTICA SINICA
, 1997
"... Classification trees based on exhaustive search algorithms tend to be biased towards selecting variables that afford more splits. As a result, such trees should be interpreted with caution. This article presents an algorithm called QUEST that has negligible bias. Its split selection strategy shares ..."
Abstract

Cited by 75 (9 self)
 Add to MetaCart
Classification trees based on exhaustive search algorithms tend to be biased towards selecting variables that afford more splits. As a result, such trees should be interpreted with caution. This article presents an algorithm called QUEST that has negligible bias. Its split selection strategy shares similarities with the FACT method, but it yields binary splits and the final tree can be selected by a direct stopping rule or by pruning. Real and simulated data are used to compare QUEST with the exhaustive search approach. QUEST is shown to be substantially faster and the size and classification accuracy of its trees are typically comparable to those of exhaustive search.
An Omnibus Test for Univariate and Multivariate Normality
, 1994
"... this paper are based on random samples. In practice, however, the tests will also be applied to regression residuals and residuals from time series models. ..."
Abstract

Cited by 53 (3 self)
 Add to MetaCart
this paper are based on random samples. In practice, however, the tests will also be applied to regression residuals and residuals from time series models.
XGvis: Interactive Data Visualization with Multidimensional Scaling
, 2001
"... this article. Section 2 gives an overview of how a user operates the XGvis system. Section 3 deals with algorithm animation, direct manipulation and perturbation of the con guration. Section 4 gives details about the cost functions and their interactively controlled parameters for transformation, s ..."
Abstract

Cited by 46 (1 self)
 Add to MetaCart
this article. Section 2 gives an overview of how a user operates the XGvis system. Section 3 deals with algorithm animation, direct manipulation and perturbation of the con guration. Section 4 gives details about the cost functions and their interactively controlled parameters for transformation, subsetting and weighting of dissimilarities. Section 5 describes diagnostics for MDS. Section 6 is about computational and systems aspects, including coordination of windows, algorithms, and large data problems. Finally, Section 7 gives a tour of applications with examples of proximity analysis, dimension reduction, and graph layout in two and more dimensions
Optimization by learning and simulation of Bayesian and Gaussian networks
, 1999
"... Estimation of Distribution Algorithms (EDA) constitute an example of stochastics heuristics based on populations of individuals every of which encode the possible solutions to the optimization problem. These populations of individuals evolve in succesive generations as the search progresses  organ ..."
Abstract

Cited by 43 (6 self)
 Add to MetaCart
Estimation of Distribution Algorithms (EDA) constitute an example of stochastics heuristics based on populations of individuals every of which encode the possible solutions to the optimization problem. These populations of individuals evolve in succesive generations as the search progresses  organized in the same way as most evolutionary computation heuristics. In opposition to most evolutionary computation paradigms which consider the crossing and mutation operators as essential tools to generate new populations, EDA replaces those operators by the estimation and simulation of the joint probability distribution of the selected individuals. In this work, after making a review of the different approaches based on EDA for problems of combinatorial optimization as well as for problems of optimization in continuous domains, we propose new approaches based on the theory of probabilistic graphical models to solve problems in both domains. More precisely, we propose to adapt algorit...
Featurebased facial expression recognition: Sensitivity analysis and experiments with a multilayer perceptron
 International Journal of Pattern Recognition and Artificial Intelligence
, 1999
"... and Gaborwaveletsbased facial expression recognition uaing multilayer perceptron”, ..."
Abstract

Cited by 32 (1 self)
 Add to MetaCart
and Gaborwaveletsbased facial expression recognition uaing multilayer perceptron”,
Visualization Methodology for Multidimensional Scaling
 JOURNAL OF CLASSIFICATION
, 2001
"... We discuss interactive techniques for ..."