Results 1 - 10 of 130,005

Satisfaction and Comparison Income

by Andrew Clark, Andrew Oswald - Journal of Public Economics , 1995
"... This paper is an attempt to test the hypothesis that utility depends on income relative to a 'comparison' or reference level. Using data on 5,000 British workers, it provides two findings. First, workers' reported satisfaction levels are shown to be inversely related to their comparis ..."
Abstract - Cited by 636 (54 self) - Add to MetaCart
This paper is an attempt to test the hypothesis that utility depends on income relative to a 'comparison' or reference level. Using data on 5,000 British workers, it provides two findings. First, workers' reported satisfaction levels are shown to be inversely related

Comparison of discrimination methods for the classification of tumors using gene expression data

by Sandrine Dudoit, Jane Fridlyand, Terence P. Speed - JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION , 2002
"... A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells for thousand ..."
Abstract - Cited by 770 (6 self) - Add to MetaCart
A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells

A comparison of document clustering techniques

by Michael Steinbach, George Karypis, Vipin Kumar - In KDD Workshop on Text Mining , 2000
"... This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means algorithm and a “bisecting ” K-means algorithm.) Our results indicate that the bisecting K-means technique is ..."
Abstract - Cited by 613 (27 self) - Add to MetaCart
This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means algorithm and a “bisecting ” K-means algorithm.) Our results indicate that the bisecting K-means technique

Stochastic volatility: likelihood inference and comparison with ARCH models

by Sangjoon Kim, Salomon Brothers, Asia Limited, Neil Shephard - Review of Economic Studies , 1998
"... In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating offse ..."
Abstract - Cited by 592 (40 self) - Add to MetaCart
In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating

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
classifiers. Some authors also proposed methods that consider all classes at once. As it is computationally more expensive to solve multiclass problems, comparisons of these methods using large-scale problems have not been seriously conducted. Especially for methods solving multiclass SVM in one step, a much

Comparison of Broadcasting Techniques for Mobile Ad Hoc Networks

by Brad Williams, Tracy Camp - MOBIHOC'02 , 2002
"... Network wide broadcasting in Mobile Ad Hoc Networks provides important control and route establishment functionality for a number of unicast and multicast protocols. Considering its wide use as a building block for other network layer protocols, the MANET community needs to standardize a single meth ..."
Abstract - Cited by 519 (4 self) - Add to MetaCart
Network wide broadcasting in Mobile Ad Hoc Networks provides important control and route establishment functionality for a number of unicast and multicast protocols. Considering its wide use as a building block for other network layer protocols, the MANET community needs to standardize a single

Comparison of Multiobjective Evolutionary Algorithms: Empirical Results

by Eckart Zitzler, Lothar Thiele, Kalyanmoy Deb , 2000
"... In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in conver ..."
Abstract - Cited by 628 (41 self) - Add to MetaCart
In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly

An empirical comparison of voting classification algorithms: Bagging, boosting, and variants.

by Eric Bauer , Philip Chan , Salvatore Stolfo , David Wolpert - Machine Learning, , 1999
"... Abstract. Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and real-world datasets. We review these algorithms and describe a large empirical study comparing several vari ..."
Abstract - Cited by 707 (2 self) - Add to MetaCart
variants in conjunction with a decision tree inducer (three variants) and a Naive-Bayes inducer. The purpose of the study is to improve our understanding of why and when these algorithms, which use perturbation, reweighting, and combination techniques, affect classification error. We provide a bias

A comparison and evaluation of multi-view stereo reconstruction algorithms.

by Steven M Seitz , Brian Curless , James Diebel , Daniel Scharstein , Richard Szeliski - In Proc. Computer Vision and Pattern Recognition ’06, , 2006
"... Abstract This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multi-v ..."
Abstract - Cited by 530 (14 self) - Add to MetaCart
Abstract This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multi

A comparison of event models for Naive Bayes text classification

by Andrew McCallum, Kamal Nigam , 1998
"... Recent work in text classification has used two different first-order probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multi-variate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e.g. Larkey ..."
Abstract - Cited by 1025 (26 self) - Add to MetaCart
Recent work in text classification has used two different first-order probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multi-variate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e
Results 1 - 10 of 130,005