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20,563
Bayesian Data Analysis
, 1995
"... I actually own a copy of Harold Jeffreys’s Theory of Probability but have only read small bits of it, most recently over a decade ago to confirm that, indeed, Jeffreys was not too proud to use a classical chi-squared p-value when he wanted to check the misfit of a model to data (Gelman, Meng and Ste ..."
Abstract
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Cited by 2194 (63 self)
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I actually own a copy of Harold Jeffreys’s Theory of Probability but have only read small bits of it, most recently over a decade ago to confirm that, indeed, Jeffreys was not too proud to use a classical chi-squared p-value when he wanted to check the misfit of a model to data (Gelman, Meng
Analysis of Recommendation Algorithms for E-Commerce
, 2000
"... Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in E-Commerce nowadays. In this paper, we investigate several techniques for analyzing large-scale pu ..."
Abstract
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Cited by 523 (22 self)
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-scale purchase and preference data for the purpose of producing useful recommendations to customers. In particular, we apply a collection of algorithms such as traditional data mining, nearest-neighbor collaborative ltering, and dimensionality reduction on two dierent data sets. The rst data set was derived from
Risks for the long run: A potential resolution of asset pricing puzzles
- JOURNAL OF FINANCE
, 1994
"... We model consumption and dividend growth rates as containing (i) a small long-run predictable component and (ii) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin’s (1989) preferences, can explain ke ..."
Abstract
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Cited by 761 (63 self)
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We model consumption and dividend growth rates as containing (i) a small long-run predictable component and (ii) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin’s (1989) preferences, can explain
The use of the area under the ROC curve in the evaluation of machine learning algorithms
- PATTERN RECOGNITION
, 1997
"... In this paper we investigate the use of the area under the receiver operating characteristic (ROC) curve (AUC) as a performance measure for machine learning algorithms. As a case study we evaluate six machine learning algorithms (C4.5, Multiscale Classifier, Perceptron, Multi-layer Perceptron, k-Ne ..."
Abstract
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Cited by 685 (3 self)
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-Nearest Neighbours, and a Quadratic Discriminant Function) on six "real world " medical diagnostics data sets. We compare and discuss the use of AUC to the more conventional overall accuracy and find that AUC exhibits a number of desirable properties when compared to overall accuracy: increased
Protecting respondents’ identities in microdata release
- In IEEE Transactions on Knowledge and Data Engineering (TKDE
, 2001
"... Today’s globally networked society places great demand on the dissemination and sharing of information. While in the past released information was mostly in tabular and statistical form, many situations call today for the release of specific data (microdata). In order to protect the anonymity of the ..."
Abstract
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Cited by 512 (32 self)
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Today’s globally networked society places great demand on the dissemination and sharing of information. While in the past released information was mostly in tabular and statistical form, many situations call today for the release of specific data (microdata). In order to protect the anonymity
Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes
, 1996
"... Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a p ..."
Abstract
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Cited by 1416 (26 self)
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, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity insuch traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in le transfer
Approximate Sorting of Preference Data
"... We consider sorting data in noisy conditions. Whereas sorting itself is a well studied topic, ordering items when the comparisons between objects can suffer from noise is a rarely addressed question. However, the capability of handling noisy sorting can be of a prominent importance, in particular in ..."
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We consider sorting data in noisy conditions. Whereas sorting itself is a well studied topic, ordering items when the comparisons between objects can suffer from noise is a rarely addressed question. However, the capability of handling noisy sorting can be of a prominent importance, in particular
Using Revealed Preference Data
"... The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors ’ own opinions and do not necessarily reflect those of the editors. Ruhr Economic Papers #99 ..."
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The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors ’ own opinions and do not necessarily reflect those of the editors. Ruhr Economic Papers #99
Analysis of Ranked Preference Data
"... This thesis is documentation for a master project, at the department of Informatics ..."
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This thesis is documentation for a master project, at the department of Informatics
Accurately interpreting clickthrough data as implicit feedback
- In Proceedings of SIGIR
, 2005
"... This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users ’ decision process using eyetracking and comparing implicit feedback against manual relevance judgments, we conclude that clicks are informative but biased. While this makes t ..."
Abstract
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Cited by 434 (7 self)
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This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users ’ decision process using eyetracking and comparing implicit feedback against manual relevance judgments, we conclude that clicks are informative but biased. While this makes
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20,563
