We develop an online variational Bayes (VB) algorithm for Latent Dirichlet Allocation (LDA). Online LDA is based on online stochastic optimization with a natural gradient step, which we show converges to a local optimum of the VB objective function. It can handily analyze massive document collections, including those arriving in a stream. We study the performance of online LDA in several ways, ...

Authorship attribution deals with identifying the authors of anonymous texts. Building on our earlier finding that the Latent Dirichlet Allocation (LDA) topic model can be used to improve authorship attribution accuracy, we show that employing a previously-suggested Author-Topic (AT) model outperforms LDA when applied to scenarios with many authors. In addition, we define a model that combines ...

In this paper, a relationship between linear discriminant analysis (LDA) and the generalized minimum squared error (MSE) solution is presented. The generalized MSE solution is shown to be equivalent to applying a certain classification rule in the space defined by LDA. The relationship between the MSE solution and Fisher discriminant analysis is extended to multiclass problems and also to under...

Minerals and some biochemical parameters determined from blood serum analyses in left displacement abomasum (LDA) affected and healthy dairy cows to evaluate the effect of displacement abomasum on mineral status, energy metabolism and liver function. Samples were collected from 60 affected cows and 60 healthy control cows matched with cases, based on herd, parity, and stage of lactation. Concen...

Left-sided displacement of the abomasum (LDA) is a common disease in many dairy cattle breeds. A genome-wide screen for QTL for LDA in German Holstein (GH) cows indicated motilin (MLN) as a candidate gene on bovine chromosome 23. Genomic DNA sequence analysis of MLN revealed a total of 32 polymorphisms. All informative polymorphisms used for association analyses in a random sample of 1,136 GH c...

OBJECTIVE To determine whether low molecular weight heparin (LMWH) plus low-dose aspirin (LDA) is comparable in efficacy and safety to unfractionated heparin (UFH) plus LDA in the management of pregnant women with a history of recurrent spontaneous abortion secondary to antiphospholipid syndrome (APS). METHODS In a randomized prospective study, 60 women with a history of 3 or more consecutive...

The method based on local features has an advantage that the important local motion feature is represented as bag-of-features, but lacks the location information. Additionally, in order to employ an approach based on bag-of-features, language models represented by pLSA and LDA (Latent Dirichlet Allocation) have to be applied to. These are unsupervised learning, but they require the number of la...

Observation of theorized glass-to-liquid transitions between low-density amorphous (LDA) and high-density amorphous (HDA) water states had been stymied by rapid crystallization below the homogeneous water nucleation temperature (∼235 K at 0.1 MPa). We report optical and X-ray observations suggestive of glass-to-liquid transitions in these states. Crack healing, indicative of liquid, occurs when...

Latent Dirichlet allocation (LDA) is a widely-used probabilistic topic modeling paradigm, and recently finds many applications in computer vision and computational biology. In this paper, we propose a fast and accurate batch algorithm, active belief propagation (ABP), for training LDA. Usually batch LDA algorithms require repeated scanning of the entire corpus and searching the complete topic s...

Linear Discriminant Analysis (LDA) and Multilinear Principal Component Analysis (MPCA) are leading subspace methods for achieving dimension reduction based on supervised learning. Both LDA and MPCA use class labels of data samples to calculate subspaces onto which these samples are projected. Furthermore, both methods have been successfully applied to face recognition. Although LDA and MPCA sha...