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99
Collective Latent Dirichlet Allocation
"... In this paper, we propose a new variant of Latent Dirichlet Allocation(LDA): Collective LDA (C-LDA), for multiple corpora modeling. C-LDA combines multiple corpora during learning such that it can transfer knowledge from one corpus to another; meanwhile it keeps a discriminative node which represent ..."
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Cited by 1 (0 self)
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represents the corpus ID to constrain the learned topics in each corpus. Compared with LDA locally applied to the target corpus, C-LDA results in refined topicword distribution, while compared with applying LDA globally and straightforwardly to the combined corpus, C-LDA keeps each topic only for one corpus
1 LDaC: A Wideband Loran Data Acquisition System
"... Loran-C provides timing and positioning services which are suitable for GPS backup in the National Airspace System (NAS). To assess the system’s ability to provide the necessary accuracy, integrity, availability and continuity, a variety of analyses and measurement tasks are underway. These tests ha ..."
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need to record and analyze wideband Loran-C signals, produce reports and databases, and make the results available to the project team for development of such documents as RTCA MOPS /
A discriminant analysis using composite features for classification problems
, 2007
"... In this paper, we propose a new discriminant analysis using composite features for pattern classification. A composite feature consists of a number of primitive features, each of which corresponds to an input variable. The covariance of composite features is obtained from the inner product of compos ..."
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Cited by 5 (2 self)
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discriminant analysis (LDA). Unlike LDA, the number of extracted features can be larger than the number of classes in C-LDA, which is a desirable property especially for binary classification problems. Experimental results on several data sets indicate that C-LDA provides better classification results than
Nonlinear Discriminant Analysis using Kernel Functions
- Advances in Neural Information Processing Systems
, 1999
"... Fishers linear discriminant analysis (LDA) is a classical multivariate technique both for dimension reduction and classication. The data vectors are transformed into a low dimensional subspace such that the class centroids are spread out as much as possible. In this subspace LDA works as a simple pr ..."
Abstract
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Cited by 99 (9 self)
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Fishers linear discriminant analysis (LDA) is a classical multivariate technique both for dimension reduction and classication. The data vectors are transformed into a low dimensional subspace such that the class centroids are spread out as much as possible. In this subspace LDA works as a simple
Feature Extraction from Time-Frequency Matrices for Robust Speech Recognition
, 2001
"... In this paper we present a study about time-frequency distribution of acoustic-phonetic information for the Spanish language. This is based on a large Spanish database automatically labeled, and we conclude that results are similar to those obtained for hand-labeled english databases. We use bidimen ..."
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this fact to reduce the dimensionality of the problem. Finally, cascade unidimensional LDA (CLDA) is applied first in frequency and then in time. This gives better estimates of projection vectors and better recognition performance. The proposed techniques are evaluated in a connected digit recognition task
Latent Dirichlet Allocation in Web Spam Filtering. manuscript
, 2008
"... Latent Dirichlet allocation (LDA) (Blei, Ng, Jordan 2003) is a fully generative statistical language model on the content and topics of a corpus of documents. In this paper we apply an extension of LDA for web spam classification. Our linked LDA technique takes also linkage into account: topics are ..."
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Cited by 24 (5 self)
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Net classifier, in terms of the AUC of classification, we achieve 3 % improvement over plain LDA with BayesNet, and 8 % over the public link features with C4.5. The addition of this method to a log-odds based combination of strong link and content baseline classifiers results in a 3 % improvement in AUC. Our
SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
- IEEE Transactions on Knowledge and Data Engineering
, 2008
"... Abstract—Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by maximizing the between-class covariance and simultaneously minimizing the within-class covariance. It has been wid ..."
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Cited by 32 (1 self)
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Abstract—Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by maximizing the between-class covariance and simultaneously minimizing the within-class covariance. It has been
COMPARISON OF VELOCITY MEASUREMENTS BY HIGH TEMPERATURE ANEMOMETER AND LASER-DOPPLER ANEMOMETER WITH RESULTS OF CFD-SIMULATION
"... In the pres ent work, re sults of gas ve loc ity mea sure ments with a newly de vel oped vane an e mom e ter (HTA – High Tem per a ture Anemometer) are com pared with re sults of mea sure ments ob tained from La ser--Dopp ler An e mom e ter (LDA). The mea sure ments were car ried out at the com bus ..."
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of 30 MW. Al though the en vi ron ment was both very hot (up to 1350 °C) and dust laden, the vane an e mom e ter worked with an ac cu racy com pa ra ble to the ref er ence LDA mea sure ment. Since the an e mom e ter rep re sents a rel a tively sim ple to use and low cost op tion com pared with LDA
M 2002 Lattice dynamics of TiO2 rutile: influence of gradient corrections in density functional calculations
"... Density functional calculations are performed for bulk TiO2 rutile. The equilibrium geometry, bulk modulus and the C-point phonons are calculated. The local density approximation (LDA) and two generalized-gradient approximations (PBE and PW91) are used to describe the exchange–correlation energy. Th ..."
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Cited by 2 (0 self)
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Density functional calculations are performed for bulk TiO2 rutile. The equilibrium geometry, bulk modulus and the C-point phonons are calculated. The local density approximation (LDA) and two generalized-gradient approximations (PBE and PW91) are used to describe the exchange–correlation energy
Synovitis and Osteitis Are Very Frequent in Rheumatoid Arthritis Clinical Remission: Results from an MRI Study of 294 Patients in Clinical Remission or Low Disease Activity State
, 2011
"... ABSTRACT Objective. In rheumatoid arthritis (RA), radiographic progression may occur despite clinical remission. This may be explained by subclinical inflammation. Magnetic resonance imaging (MRI) provides a greater sensitivity than clinical examination and radiography for assessing disease activit ..."
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activity. Our objective was to determine the MRI characteristics of RA patients in clinical remission or low disease activity (LDA) state. Methods. Databases from 6 cohorts were collected from 5 international centers. RA patients in clinical remission according to Disease Activity Score28-C
Results 1 - 10
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99