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» Learning to learn with the informative vector machine
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JMLR
2012
13 years 9 months ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
186
Voted
CIARP
2008
Springer
15 years 9 months ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
CIKM
2008
Springer
15 years 9 months ago
Group-based learning: a boosting approach
This paper points out that many machine learning problems in IR should be and can be formalized in a novel way, referred to as `group-based learning'. In group-based learning...
Weijian Ni, Jun Xu, Hang Li, Yalou Huang
ICML
2005
IEEE
16 years 7 months ago
Interactive learning of mappings from visual percepts to actions
We introduce flexible algorithms that can automatically learn mappings from images to actions by interacting with their environment. They work by introducing an image classifier i...
Justus H. Piater, Sébastien Jodogne
223
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UAI
2004
15 years 8 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby