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» Learning to learn with the informative vector machine
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IJCNN
2000
IEEE
15 years 10 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio
ICML
2007
IEEE
16 years 7 months ago
Learning to combine distances for complex representations
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
BMCBI
2010
179views more  BMCBI 2010»
15 years 6 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
MANSCI
2006
180views more  MANSCI 2006»
15 years 6 months ago
Selectively Acquiring Customer Information: A New Data Acquisition Problem and an Active Learning-Based Solution
This paper presents a new information acquisition problem motivated by business applications where customer data has to be acquired with a specific modeling objective in mind. In ...
Zhiqiang Zheng, Balaji Padmanabhan
139
Voted
ALT
2003
Springer
15 years 9 months ago
Efficiently Learning the Metric with Side-Information
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
Tijl De Bie, Michinari Momma, Nello Cristianini