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92
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ICML
2006
IEEE
16 years 1 months ago
An analysis of graph cut size for transductive learning
I consider the setting of transductive learning of vertex labels in graphs, in which a graph with n vertices is sampled according to some unknown distribution; there is a true lab...
Steve Hanneke
97
Voted
CVPR
2007
IEEE
16 years 2 months ago
Learning Kernel Expansions for Image Classification
Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
Fernando De la Torre, Oriol Vinyals
120
Voted
BMCBI
2011
14 years 4 months ago
Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
184
Voted
ICML
2002
IEEE
16 years 1 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
98
Voted
ECML
2006
Springer
15 years 4 months ago
Bandit Based Monte-Carlo Planning
Abstract. For large state-space Markovian Decision Problems MonteCarlo planning is one of the few viable approaches to find near-optimal solutions. In this paper we introduce a new...
Levente Kocsis, Csaba Szepesvári