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» Computationally Efficient Transductive Machines
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ICPR
2008
IEEE
14 years 9 months ago
Efficient user preference predictions using collaborative filtering
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
C. Lee Giles, Yang Song
ICIP
2009
IEEE
13 years 5 months ago
Efficient reduction of support vectors in kernel-based methods
Kernel-based methods, e.g., support vector machine (SVM), produce high classification performances. However, the computation becomes time-consuming as the number of the vectors su...
Takumi Kobayashi, Nobuyuki Otsu
ICML
2009
IEEE
14 years 8 months ago
Prototype vector machine for large scale semi-supervised learning
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Kai Zhang, James T. Kwok, Bahram Parvin
SIGIR
2003
ACM
14 years 29 days ago
Question classification using support vector machines
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Dell Zhang, Wee Sun Lee
ICML
2009
IEEE
14 years 8 months ago
Factored conditional restricted Boltzmann Machines for modeling motion style
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
Graham W. Taylor, Geoffrey E. Hinton