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» Evaluating algorithms that learn from data streams
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BMCBI
2011
15 years 1 months ago
Learning genetic epistasis using Bayesian network scoring criteria
Background: Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have be...
Xia Jiang, Richard E. Neapolitan, M. Michael Barma...
IROS
2008
IEEE
110views Robotics» more  IROS 2008»
16 years 1 months ago
Interacting with a mobile robot: Evaluating gestural object references
— Creating robots able to interact and cooperate with humans in household environments and everyday life is an emerging topic. Our goal is to facilitate a humanlike and intuitive...
Joachim Schmidt, Nils Hofemann, Axel Haasch, Janni...
ICDM
2005
IEEE
117views Data Mining» more  ICDM 2005»
16 years 9 days ago
On Learning Asymmetric Dissimilarity Measures
Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measure...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
ICCV
2009
IEEE
16 years 11 months ago
Is that you? Metric Learning Approaches for Face Identification
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background...
Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmi...
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
15 years 5 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas