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SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
15 years 6 months ago
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
SDM
2008
SIAM
105views Data Mining» more  SDM 2008»
15 years 6 months ago
Gaussian Process Learning for Cyber-Attack Early Warning
Network security has been a serious concern for many years. For example, firewalls often record thousands of exploit attempts on a daily basis. Network administrators could benefi...
Jian Zhang 0004, Phillip A. Porras, Johannes Ullri...
SDM
2007
SIAM
89views Data Mining» more  SDM 2007»
15 years 6 months ago
Preventing Information Leaks in Email
The widespread use of email has raised serious privacy concerns. A critical issue is how to prevent email information leaks, i.e., when a message is accidentally addressed to non-...
Vitor R. Carvalho, William W. Cohen
FLAIRS
2004
15 years 6 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
15 years 6 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
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