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BMCBI
2010
182views more  BMCBI 2010»
13 years 7 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
PKDD
2005
Springer
109views Data Mining» more  PKDD 2005»
14 years 1 months ago
An Imbalanced Data Rule Learner
Imbalanced data learning has recently begun to receive much attention from research and industrial communities as traditional machine learners no longer give satisfactory results. ...
Canh Hao Nguyen, Tu Bao Ho
ICML
2007
IEEE
14 years 8 months ago
Simpler core vector machines with enclosing balls
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
András Kocsor, Ivor W. Tsang, James T. Kwok
ICML
2007
IEEE
14 years 8 months ago
Piecewise pseudolikelihood for efficient training of conditional random fields
Discriminative training of graphical models can be expensive if the variables have large cardinality, even if the graphical structure is tractable. In such cases, pseudolikelihood...
Charles A. Sutton, Andrew McCallum
AGENTS
2000
Springer
13 years 12 months ago
Adaptivity in agent-based routing for data networks
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems MAS's in noisy environme...
David Wolpert, Sergey Kirshner, Christopher J. Mer...