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EMNLP
2008
15 years 8 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
BMCBI
2010
98views more  BMCBI 2010»
15 years 6 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
JMLR
2006
132views more  JMLR 2006»
15 years 6 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
164
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SIGCSE
2010
ACM
186views Education» more  SIGCSE 2010»
16 years 1 months ago
Teaching operating systems using virtual appliances and distributed version control
Students learn more through hands-on project experience for computer science courses such as operating systems, but providing the infrastructure support for a large class to learn...
Oren Laadan, Jason Nieh, Nicolas Viennot
ACL
2006
15 years 8 months ago
URES : an Unsupervised Web Relation Extraction System
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these a...
Binyamin Rosenfeld, Ronen Feldman