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An interesting observation about the well-known AdaBoost algorithm is that, though theory suggests it should overfit when applied to noisy data, experiments indicate it often does not do so in practice. In this paper, we study the behavior of AdaBoost on datasets with one-sided uniform class noise using linear classifiers as the base learner. We show analytically that, under some ideal conditions,...
In networked multiagent societies, how global social order (i.e., social norm) can be achieved through agents' local interactions is a critical research problem in multiagent systems. It has been shown that learning from individual local interactions is an effective mechanism to facilitate norm emergence. Most of the existing work, however, mainly focuses on studying norm emergence via agent learning...
Network clustering is an important problem thathas recently drawn a lot of attentions. Most existing workfocuses on clustering nodes within a single network. In manyapplications, however, there exist multiple related networks, inwhich each network may be constructed from a different domainand instances in one domain may be related to instances in otherdomains. In this paper, we propose a robust algorithm,...
Feature selection plays an important role in machinelearning applications. Especially for text data, the highdimensionaland sparse characteristics will affect the performanceof feature selction. In this paper, an unsupervised feature selection algorithm through Random Projection and Gram-Schmidt Orthogonalization (RP-GSO) from the word co-occurrence matrix is proposed. The RP-GSO has three advantages:...
With the rapid development of EDA technology, many universities have set up the digital design course in the computer science speciality. The digital design course needs SOPC system board to mount FPGA and the appropriate support circuitry. This paper presented the design of extensible SOPC system board. This board has compact structure and embodies the characteristics of SOPC system such as high...
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