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JCP
2006
102views more  JCP 2006»
15 years 6 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo
NECO
2008
112views more  NECO 2008»
15 years 6 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel
TSD
2010
Springer
15 years 4 months ago
Correlation Features and a Linear Transform Specific Reproducing Kernel
Abstract. In this paper we introduce two ideas for phoneme classification: First, we derive the necessary steps to integrate linear transform into the computation of reproducing ke...
Andreas Beschorner, Dietrich Klakow
ALMOB
2008
69views more  ALMOB 2008»
15 years 7 months ago
Learning from positive examples when the negative class is undetermined- microRNA gene identification
Background: The application of machine learning to classification problems that depend only on positive examples is gaining attention in the computational biology community. We an...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
FOCS
2010
IEEE
15 years 4 months ago
Learning Convex Concepts from Gaussian Distributions with PCA
We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
Santosh Vempala