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NIPS
1998
15 years 7 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
178
Voted
UAI
2000
15 years 7 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
155
Voted
CRYPTO
2010
Springer
188views Cryptology» more  CRYPTO 2010»
15 years 7 months ago
i-Hop Homomorphic Encryption and Rerandomizable Yao Circuits
Homomorphic encryption (HE) schemes enable computing functions on encrypted data, by means of a public Eval procedure that can be applied to ciphertexts. But the evaluated ciphert...
Craig Gentry, Shai Halevi, Vinod Vaikuntanathan
ADCM
2010
90views more  ADCM 2010»
15 years 6 months ago
Local reconstruction for sampling in shift-invariant spaces
The local reconstruction from samples is one of most desirable properties for many applications in signal processing, but it has not been given as much attention. In this paper, we...
Qiyu Sun
BMCBI
2010
126views more  BMCBI 2010»
15 years 6 months ago
A boosting method for maximizing the partial area under the ROC curve
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Osamu Komori, Shinto Eguchi