Special Issue on Learning from Multiple Sources; Guest Editors: Nicolò Cesa-Bianchi, David R. Hardoon, and Gayle Leen
1-3
Editorial
Guest Editorial: Learning from multiple sources
Nicolò Cesa-Bianchi, David R. Hardoon and Gayle Leen
5-27
Open AccessTemporal kernel CCA and its application in multimodal neuronal data analysis
Felix Bießmann, Frank C. Meinecke, Arthur Gretton, Alexander Rauch and Gregor Rainer, et al.
29-46
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
David R. Hardoon and John Shawe-Taylor
47-71
Open AccessMulti-view kernel construction
Virginia R. de Sa, Patrick W. Gallagher, Joshua M. Lewis and Vicente L. Malave
73-103
Composite kernel learning
Marie Szafranski, Yves Grandvalet and Alain Rakotomamonjy
105-121
A co-classification approach to learning from multilingual corpora
Massih-Reza Amini and Cyril Goutte
123-149
Multi-domain learning by confidence-weighted parameter combination
Mark Dredze, Alex Kulesza and Koby Crammer
151-175
Open AccessA theory of learning from different domains
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza and Fernando Pereira, et al.
177-200
Ensemble clustering using semidefinite programming with applications
Vikas Singh, Lopamudra Mukherjee, Jiming Peng and Jinhui Xu
201-226
Infinite factorization of multiple non-parametric views
Simon Rogers, Arto Klami, Janne Sinkkonen, Mark Girolami and Samuel Kaski
227-255
Inductive transfer for learning Bayesian networks
Roger Luis, L. Enrique Sucar and Eduardo F. Morales