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In this paper, we extend the sequential multitask learning model called Resource Allocating Network for Multi-Task Pattern Recognition (RAN-MTPR) proposed by Nishikawa et al. such that it can learn a training sample with multiple class labels which are originated from different lassification tasks. Here, we assume that no task information is given for(More)
In recent years, the use of Weblog is increasing rapidly and some people are using functions to record referer (URL of the page that the site visitor was viewing immediately before) and create back-links to the URL. Recently, as the main purpose to guide visitors to harmful sites, people are using this function to misinterpret referer information and access(More)
In this work, we extend the sequential multitask learning model called Resource Allocating Network for Multi-Task Pattern Recognition (RAN-MTPR) by introducing the following new learning functions: multi-label recognition, semi-supervised task learning and active learning. The extended RAN-MTPR can learn a training data with multiple class labels, can(More)
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