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NIPS
1994
14 years 11 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
JMLR
2010
185views more  JMLR 2010»
14 years 4 months ago
HMMPayl: an application of HMM to the analysis of the HTTP Payload
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Davide Ariu, Giorgio Giacinto
EMNLP
2008
14 years 11 months ago
Joint Unsupervised Coreference Resolution with Markov Logic
Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsupervised approaches have been proposed (e.g., Haghighi...
Hoifung Poon, Pedro Domingos
CORR
2002
Springer
132views Education» more  CORR 2002»
14 years 9 months ago
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Marco Zaffalon, Marcus Hutter
CVPR
2004
IEEE
15 years 11 months ago
A Model for Dynamic Shape and Its Applications
Variation in object shape is an important visual cue for deformable object recognition and classification. In this paper, we present an approach to model gradual changes in the ?-...
Che-Bin Liu, Narendra Ahuja