Machine Learning, Volume 79, 2010

Volume 79, Numbers 1-2, May 2010

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

Volume 79, Number 3, June 2010

• Dragos D. Margineantu, Weng-Keen Wong, Denver Dash:
  Machine learning algorithms for event detection. 257-259
  
• Daniel B. Neill, Gregory F. Cooper:
  A multivariate Bayesian scan statistic for early event detection and characterization. 261-282
  
• Daniel Nikovski, Ankur Jain:
  Fast adaptive algorithms for abrupt change detection. 283-306
  
• Gaurav Tandon, Philip K. Chan:
  Increasing coverage to improve detection of network and host anomalies. 307-334
  
• Tomás Singliar, Milos Hauskrecht:
  Learning to detect incidents from noisily labeled data. 335-354
  

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