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Classical dictionary learning algorithms that rely on a single source of information have been successfully used for the discriminative tasks. However, exploiting multiple sources has demonstrated its effectiveness in solving challenging real-world situations. We propose a new framework for feature fusion to achieve better classification performance as compared to the case where individual sources...
In silicon testing, a Shmoo plot is commonly used to give us an insight into the silicon manufacturing development health. Shmoo plots and other silicon characterization data has high value, however, analysis of them is a time-consuming work. This paper establishes a machine learning based model to improve and automate the procedure in silicon data analysis for HVM test content development. Our experiment...
The feedforward neural networks trained with the online backpropagation (BP) learning algorithm have been widely studied in various areas of scientific research and engineering applications. In this paper we further study the convergence property of the online BP learning algorithm. Unlike the existing convergence analysis mainly focusing on the convergence of the gradient sequence of the error functions,...
To improve efficiency and quality of case retrieval in case-based reasoning system, a case retrieval model based on the artificial neural network (ANN) and nearest neighbor (NN) algorithm is presented. Firstly, the indexes of cases are created in order to shrink the case-searching range, and the BP neural network is applied to memorize the product cases that are indexed. Secondly, the similar cases,...
Since malicious shill bidding behaviors changes frequently, we need a profiling mechanism to profile malicious bidders' behaviors. In this study, we apply the self-organizing map (SOM) based on shilling features to propose a profiled malicious bidder behavior model. Via this model, the auctioneer can realize the changed malicious bidder behaviors and devise detection method for detecting malicious...
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