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» Learning aspect models with partially labeled data
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NIPS
1998
13 years 8 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
MICCAI
2008
Springer
14 years 8 months ago
Cortical Surface Thickness as a Classifier: Boosting for Autism Classification
We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the...
Vikas Singh, Lopamudra Mukherjee, Moo K. Chung
IR
2010
13 years 5 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
RAID
2009
Springer
14 years 1 months ago
Autonomic Intrusion Detection System
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
Wei Wang 0012, Thomas Guyet, Svein J. Knapskog
SIGSOFT
2009
ACM
14 years 8 months ago
Fair and balanced?: bias in bug-fix datasets
Software engineering researchers have long been interested in where and why bugs occur in code, and in predicting where they might turn up next. Historical bug-occurence data has ...
Christian Bird, Adrian Bachmann, Eirik Aune, John ...