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CHI
2010
ACM
14 years 2 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
IJCAI
2007
13 years 8 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
CHI
2008
ACM
14 years 7 months ago
Investigating statistical machine learning as a tool for software development
As statistical machine learning algorithms and techniques continue to mature, many researchers and developers see statistical machine learning not only as a topic of expert study,...
Kayur Patel, James Fogarty, James A. Landay, Bever...
CVPR
2005
IEEE
14 years 9 months ago
Machine Learning for Clinical Diagnosis from Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing ...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, No...