INTERSPEECHGaussian Mixture Optimization for HMM based on Efficient Cross-validation Takahiro Shinozaki∗ , Tatsuya Kawahara Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan ∗

Source URL: www.ar.media.kyoto-u.ac.jp

UDCMICROSTRUCTURE AND CHARACTERISTICS OF Zr-1%Nb ALLOY, WHICH WAS SYNTHESIZED FROM HETEROGENEOUS POWDER MIXTURE O.M. Ivasishin1, V.M. Voyevodin2,3, P.E. Markovsky1, M.M. Pylypenko2, D.G. Savvakin1,

Source URL: vant.kipt.kharkov.ua

Image and Vision Computing–97 www.elsevier.com/locate/imavis An observation-constrained generative approach for probabilistic classification of image regions Sanjiv Kumara,*, Alexander C. Louib, Martial He

Source URL: www.sanjivk.com

• Probability and statistics
• Segmentation
• Generative model
• Mixture model
• Minimum description length
• Unsupervised learning
• Expectation–maximization algorithm
• Statistical classification
• Supervised learning
• Machine learning
• Statistics
• Computational statistics

Remote Sensing of Environment – 77 www.elsevier.com/locate/rse On the choice of spatial and categorical scale in remote sensing land cover classification Junchang Jua,T, Sucharita Gopala, Eric D. Kolaczykb

Source URL: people.bu.edu

• Probability and statistics
• Geography
• Segmentation
• Remote sensing
• Map
• Level of measurement
• Mixture model
• Scale model
• Statistics
• Cartography
• Image processing

Parametric Herding Yutian Chen Max Welling Bren School of Information and Computer Science University of California, Irvine

Source URL: www.ics.uci.edu

• Machine learning
• Econometrics
• M-estimators
• Regression analysis
• Mixture model
• Maximum likelihood
• Boltzmann machine
• Expectation–maximization algorithm
• Vector quantization
• Statistics
• Estimation theory
• Statistical theory

Randomized Algorithms for Fast Bayesian Hierarchical Clustering Katherine A. Heller and Zoubin Ghahramani Gatsby Computational Neuroscience Unit University College London, London, WC1N 3AR, UK {heller,zoubin}@gatsby.ucl.

Source URL: www.gatsby.ucl.ac.uk

• Data mining
• Geostatistics
• Hierarchical clustering
• Mixture model
• Unsupervised learning
• Randomized algorithm
• Data stream clustering
• Consensus clustering
• Statistics
• Machine learning
• Cluster analysis

According to EC-RegulationREACH) SAFETY DATA SHEET SECTION 1: Identification of the substance/mixture and of the company/undertaking 1.1. Product identifier Trade name

Source URL: www.chymeia.dk

• Occupational safety and health
• Soil contamination
• Environmental law
• Material safety data sheet
• Materials
• Safety engineering
• Solvent
• Styrene
• Toxicity
• Chemistry
• Safety
• Health

Exchangeable Inconsistent Priors for Bayesian Posterior Inference Max Welling Ian Porteous

Source URL: www.ics.uci.edu

• Dirichlet process
• Poisson distribution
• Principle of maximum entropy
• Prior probability
• Normal distribution
• Mixture model
• Gibbs sampling
• Empirical Bayes method
• Bayesian inference
• Statistics
• Probability and statistics
• Bayesian statistics

Incremental Learning of Nonparametric Bayesian Mixture Models Ryan Gomes∗ Max Welling† ∗

Source URL: www.ics.uci.edu

• Cluster analysis
• Data analysis
• Estimation theory
• Expectation–maximization algorithm
• Dirichlet process
• Variational Bayesian methods
• Mixture model
• Principal component analysis
• Kernel principal component analysis
• Statistics
• Multivariate statistics
• Machine learning

Distributed and Adaptive Darting Monte Carlo through Regenerations Sungjin Ahn Department of Computer Science University of California, Irvine Irvine, CA, USA

Source URL: www.ics.uci.edu

• Markov models
• Markov chain Monte Carlo
• Computational statistics
• Markov processes
• Markov chain
• Metropolis–Hastings algorithm
• Rejection sampling
• Mixture model
• Random walk
• Statistics
• Probability and statistics
• Monte Carlo methods