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CONEXT
2007
ACM
15 years 8 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
COLING
2002
15 years 6 months ago
Study of Practical Effectiveness for Machine Translation Using Recursive Chain-link-type Learning
A number of machine translation systems based on the learning algorithms are presented. These methods acquire translation rules from pairs of similar sentences in a bilingual text...
Hiroshi Echizen-ya, Kenji Araki, Yoshio Momouchi, ...
CICLING
2010
Springer
15 years 9 months ago
Identification of Translationese: A Machine Learning Approach
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
Iustina Ilisei, Diana Inkpen, Gloria Corpas Pastor...
SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
13 years 8 months ago
Large-scale machine learning at twitter
The success of data-driven solutions to difficult problems, along with the dropping costs of storing and processing massive amounts of data, has led to growing interest in largesc...
Jimmy Lin, Alek Kolcz
JMLR
2010
125views more  JMLR 2010»
15 years 1 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi