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» Semi-supervised Learning from General Unlabeled Data
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ML
2006
ACM
110views Machine Learning» more  ML 2006»
13 years 8 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
13 years 9 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
CVPR
2008
IEEE
14 years 10 months ago
Clustering and dimensionality reduction on Riemannian manifolds
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
Alvina Goh, René Vidal
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
14 years 8 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
ECAI
2006
Springer
13 years 11 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani