BOUNDS ON THE NUMBER OF INFERENCE FUNCTIONS OF A GRAPHICAL MODEL SERGI ELIZALDE AND KEVIN WOODS Abstract. Directed and undirected graphical models, also called Bayesian networks and Markov random fields, respectively, ar

Source URL: asoc-fulbright.es

• Bayesian statistics
• Networks
• Markov models
• Statistical models
• Hidden Markov model
• Markov random field
• Bayesian network
• Parameter
• Markov chain
• Statistics
• Graphical models
• Probability and statistics

Microsoft Word - Reference-IJDAR

Source URL: www.lhncbc.nlm.nih.gov

• Information
• Information retrieval
• Compiler construction
• Parsing
• Conditional random field
• Algorithm
• Search engine indexing
• BLAST
• Support vector machine
• Science
• Information science
• Theoretical computer science

Finding Structure in Report Transcripts

Source URL: www.ofai.at

• Conditional random field
• Clinical Data Management
• Mathematics
• Algorithm
• Case report form
• Learning
• Theoretical computer science
• Graphical models
• Machine learning

Effect of Random Errors in Planar Near–Field Measurement

Source URL: www.nist.gov

Derivative Kernels for Noise Robust ASR A. Ragni and M. J. F. Gales Cambridge University Engineering Department Trumpington St., Cambridge CB2 1PZ, U.K. {ar527,mjfg}@eng.cam.ac.uk

Source URL: mi.eng.cam.ac.uk

• Computational linguistics
• Speech recognition
• Markov models
• Bioinformatics
• Hidden Markov model
• Generative model
• Discriminative model
• Conditional random field
• N-gram
• Machine learning
• Statistics
• Probability

Structured Support Vector Machines for Noise Robust Continuous Speech Recognition Shi-Xiong Zhang and Mark Gales Department of Engineering, University of Cambridge, Cambridge, UK {sxz20, mjfg}@eng.cam.ac.uk

Source URL: mi.eng.cam.ac.uk

• Statistical classification
• Support vector machines
• Bioinformatics
• Markov models
• Hidden Markov model
• Structured SVM
• Speech recognition
• Conditional random field
• Maximum likelihood
• Statistics
• Machine learning
• Probability and statistics

INFERENCE ALGORITHMS FOR GENERATIVE SCORE-SPACES A. Ragni and M. J. F. Gales Cambridge University Engineering Department Trumpington St., Cambridge CB2 1PZ, U.K. {ar527,mjfg}@eng.cam.ac.uk ABSTRACT

Source URL: mi.eng.cam.ac.uk

• Markov models
• Computational linguistics
• Estimation theory
• Bioinformatics
• Hidden Markov model
• Conditional random field
• Generative model
• N-gram
• Maximum likelihood
• Statistics
• Machine learning
• Probability

Appendix 1: Random Street Segments Workbook These instructions are designed to help users of all skill levels create random i-Tree Streets (STRATUM) sample street segments for use in field data collection. ESRI ArcGIS so

Source URL: www.itreetools.org

• Cartography
• Geographic information system
• ArcGIS
• Shapefile
• Geodatabase
• ArcMap
• Topologically Integrated Geographic Encoding and Referencing
• HTML element
• Science
• GIS software
• GIS file formats
• Computing

Assessing Vaccination Coverage Levels Using Clustered Lot Quality Assurance Sampling Field Manual VERSION EDITED FOR THE GLOBAL POLIO

Source URL: www.polioeradication.org

• Poliomyelitis
• Survey methodology
• Lot quality assurance sampling
• Poliomyelitis eradication
• Cluster sampling
• Polio vaccine
• Vaccination
• Simple random sample
• Sample
• Statistics
• Sampling
• Market research

Progress In Electromagnetics Research B, Vol. 29, 251–267, 2011 MODELING OF THE HUMAN EXPOSURE INSIDE A RANDOM PLANE WAVE FIELD F. Moglie, V. Mariani Primiani, and A. P. Pastore Dipartimento di Ingegneria Biomedica, E

Source URL: www.jpier.org

• Partial differential equations
• Length
• Wavelength
• Waves
• Antenna
• Polarization
• Normal distribution
• Electromagnetic radiation
• Wave
• Physics
• Calculus
• Mathematical analysis