Sophisticated big data machine learning applications are difficult to parallelize because it not only needs to process a big training dataset, it also needs to synchronize big model data in iterations. In parallel LDA, comparing synchronized and asynchronous communication methods under data parallelism and model parallelism, we note that the power-law distribution of word counts in LDA training...

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high ...

Linear Discriminant Analysis (LDA) is a well-known technique to improve the discrimination among classes or reduce the dimensionality with minimum loss of discrimination. It is generally used as a part of the front-end of speech recognizer with the classes defined on phone or subphone level. LDA with subphone-level classes (such as tied states or individual Gaussian densities) shows superior pe...

Copyright: 2014 The PLOS ONE Staff. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Figure 3. Topics learnxled by Red-LDA (top) and Vanilla LDA (bottom) on the EHR corpus. Both topics are about breast cancer (...

BACKGROUND Several lines of evidence suggest that male embryos may have greater vulnerability than female embryos to disordered inflammation; therefore, antiinflammatory drugs, such as low-dose aspirin (LDA), may alter the sex ratio. Here, we assessed the effect of LDA on male live birth and male offspring, incorporating pregnancy losses (n = 56) via genetic assessment, as part of a parallel-de...

The advent of the Social Web has provided netizens with new tools for creating and sharing, in a timeand costefficient way, their contents, ideas, and opinions with virtually the millions of people connected to the World Wide Web. This huge amount of information, however, is mainly unstructured as specifically produced for human consumption and, hence, it is not directly machine-processable. In...

BACKGROUND Usually the training set of online brain-computer interface (BCI) experiment is small. For the small training set, it lacks enough information to deeply train the classifier, resulting in the poor classification performance during online testing. METHODS In this paper, on the basis of Z-LDA, we further calculate the classification probability of Z-LDA and then use it to select the ...

Latent Dirichlet Allocation (LDA) is a method that can be used to generate word association networks from unstructured text documents. However, no study has yet examined the applicability of LDA for deriving product associations from user-generated content. In this work, we apply LDA on 9,529 unstructured and uncategorized McDonald’s product reviews that were crawled from a German online review...

In this paper we describe a face recognition method based on PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis). The method consists of two steps: rst we project the face image from the original vector space to a face subspace via PCA, second we use LDA to obtain a best linear clas-siier. The basic idea of combining PCA and LDA is to improve the generalization capability ...