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NAACL
2004
14 years 11 months ago
Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization
We consider the problem of modeling the content structure of texts within a specific domain, in terms of the topics the texts address and the order in which these topics appear. W...
Regina Barzilay, Lillian Lee
ICTAI
2007
IEEE
15 years 3 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
CBMS
2008
IEEE
14 years 11 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
BMCBI
2010
118views more  BMCBI 2010»
14 years 9 months ago
Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry
Background: There is an increasing usage of ion mobility-mass spectrometry (IMMS) in proteomics. IMMS combines the features of ion mobility spectrometry (IMS) and mass spectrometr...
Bing Wang, Steve Valentine, Manolo Plasencia, Srir...
SIGMETRICS
2008
ACM
142views Hardware» more  SIGMETRICS 2008»
14 years 9 months ago
Exploiting manufacturing variations for compensating environment-induced clock drift in time synchronization
Time synchronization is an essential service in distributed computing and control systems. It is used to enable tasks such as synchronized data sampling and accurate time-offlight...
Thomas Schmid, Zainul Charbiwala, Jonathan Friedma...