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» Learning to learn with the informative vector machine
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ICPR
2010
IEEE
16 years 9 days ago
RBM-Based Silhouette Encoding for Human Action Modelling
—In this paper we evaluate the use of Restricted Bolzmann Machines (RBM) in the context of learning and recognizing human actions. The features used as basis are binary silhouett...
Manuel Jesus Marin-Jimenez, Nicolas Perez De La Bl...
AIME
2009
Springer
15 years 11 months ago
The Role of Biomedical Dataset in Classification
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...
Ajay Kumar Tanwani, Muddassar Farooq
179
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CSB
2005
IEEE
126views Bioinformatics» more  CSB 2005»
16 years 18 days ago
Identifying Simple Discriminatory Gene Vectors with an Information Theory Approach
In the feature selection of cancer classification problems, many existing methods consider genes individually by choosing the top genes which have the most significant signal-to...
Zheng Yun, Kwoh Chee Keong
IJCAI
2003
15 years 8 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
CN
2010
110views more  CN 2010»
15 years 7 months ago
End-to-end quality of service seen by applications: A statistical learning approach
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...
Pablo Belzarena, Laura Aspirot