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SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
11 years 11 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
MODELLIERUNG
2004
13 years 10 months ago
Modeling Socio-Technical Processes in e-Commerce Scenarios
: We consider socio-technical processes, i.e. processes where machines as well as humans participate. Typical examples occur in sales processes in e-commerce. Three modeling tasks ...
Michael M. Richter, Armin Stahl
ECML
2005
Springer
14 years 2 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
WMCSA
2008
IEEE
14 years 3 months ago
HealthSense: classification of health-related sensor data through user-assisted machine learning
Remote patient monitoring generates much more data than healthcare professionals are able to manually interpret. Automated detection of events of interest is therefore critical so...
Erich P. Stuntebeck, John S. Davis II, Gregory D. ...
BMCBI
2008
173views more  BMCBI 2008»
13 years 9 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...