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Topic models such as LDA have been widely used to capture latent topics in textual collections. Due to the large scale of data, researchers begin to pay more attention to speed up the efficiency of LDA Gibbs sampling by parallel inference algorithms or distributed computing. In this paper, we improve the traditional Approximate Distributed LDA (AD-LDA) algorithm by introducing weighted factor during...
Image annotation has attracted a lot of research interest, and multi-label learning is an effective technique for image annotation. How to effectively exploit the underlying correlation among labels is a crucial task for multi-label learning. Most existing multi-label learning methods exploit the label correlation only in the output label space, leaving the connection between the label and the features...
By making use of the characteristic of the cost function MSSO (Mean of the Square Soft Outputs), a new method of carrier phase synchronization and decoding for the turbo-coded systems is presented. Firstly, a short training sequence is used to achieve the initial phase estimation and to narrow the phase searching range. Secondly, three decoding sequences with the largest MSSO values are chosen by...
A series of support vector machine (SVM) forecast experiments are carried out to reveal the relation between the SVM training sample size and SVM correct forecast ratio for simulation experiment results. Experiment results show that the SVM correct forecast ratio increases to some extent with the number of training samples becoming more and then keeps unchanged even if the SVM training sample number...
Information fusion has been widely applied in many fields. Aggregate operator plays a key role in information fusion. So far, all existing aggregate operators are defined on a subset of a space (set). In many of the problems with information fusion, we often need to deal with the operator defined on a partition of the space. Motivated by minimizing the classification information entropy of a partition...
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