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M-estimators
Results: 330

#	Item
201	Lifted Online Training of Relational Models with Stochastic Gradient Methods Babak Ahmadi1 , Kristian Kersting1,2,3 , and Sriraam Natarajan3 1 2 Add to Reading List Source URL: first-mm.informatik.uni-freiburg.de Language: English - Date: 2012-07-18 11:37:23 Machine learning Theoretical computer science M-estimators Maximum likelihood Markov random field Statistical relational learning Conditional random field Stochastic gradient descent Belief propagation Statistics Graphical models Statistical models
202	III JIPE MINIMUM DISTANCE ESTIMATION OF HIGH FREQUENCY TRANSACTION DATA Mauricio Zevallos Universidade Estadual de Campinas, Brasil Add to Reading List Source URL: jornada.pucp.edu.pe Language: English - Date: 2014-08-08 10:56:39 M-estimators Mathematical modeling Minimum distance estimation Maximum likelihood Estimator Estimation theory Statistics Statistical inference
203	Ph.D. Methodology Qualifying Exam, August 2011 Department of Statistics, Texas A&M University Instruction 1. DO NOT put your NAME on the exam. Place the NUMBER assigned to you on the UPPER RIGHT HAND CORNER of EACH PAGE Add to Reading List Source URL: www.stat.tamu.edu Language: English - Date: 2011-09-06 11:51:13 M-estimators Maximum likelihood Bias of an estimator Normal distribution Support Expectation–maximization algorithm Exponential distribution Statistics Estimation theory Statistical theory
204	Lifted Parameter Learning in Relational Models Babak Ahmadi1 [removed] Kristian Kersting1,2,3 [removed] Add to Reading List Source URL: www.first-mm.eu Language: English - Date: 2012-07-18 13:16:28 Theoretical computer science M-estimators Stochastic optimization Estimation theory Stochastic gradient descent Markov logic network Conditional random field Gradient boosting Maximum likelihood Statistics Machine learning Probability and statistics
205	Lifted Online Training of Relational Models with Stochastic Gradient Methods Babak Ahmadi1 , Kristian Kersting1,2,3 , and Sriraam Natarajan3 1 2 Add to Reading List Source URL: www.first-mm.eu Language: English - Date: 2012-07-18 11:37:23 Machine learning Theoretical computer science M-estimators Maximum likelihood Markov random field Statistical relational learning Conditional random field Stochastic gradient descent Belief propagation Statistics Graphical models Statistical models
206	Lifted Parameter Learning in Relational Models Babak Ahmadi1 [removed] Kristian Kersting1,2,3 [removed] Add to Reading List Source URL: first-mm.informatik.uni-freiburg.de Language: English - Date: 2012-07-18 13:16:28 Theoretical computer science M-estimators Stochastic optimization Estimation theory Stochastic gradient descent Markov logic network Conditional random field Gradient boosting Maximum likelihood Statistics Machine learning Probability and statistics
207	Package ‘GPvam’ July 2, 2014 Type Package Title Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling Version 3.0-2 Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 09:50:53 Analysis of variance Statistical methods M-estimators Expectation–maximization algorithm Generalized linear mixed model Mixed model Maximum likelihood Statistics Regression analysis Estimation theory
208	The Influence of Space and Time Varying Distortions on Objective Intelligibility Estimators for Region-of-Interest Video Frank M. Ciaramello and Sheila S. Hemami Visual Communications Lab, School of Electrical and Comput Add to Reading List Source URL: foulard.ece.cornell.edu Language: English - Date: 2010-11-16 16:04:35 Statistics Estimation theory Videotelephony Rate–distortion optimization X264 Electronic engineering H.264/MPEG-4 AVC Estimator Distortion Video compression Statistical inference Video
209	Package ‘MARSS’ July 2, 2014 Type Package Title Multivariate Autoregressive State-Space Modeling Version 3.9 Date[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 10:00:15 Statistical theory Markov models Multivariate normal distribution Normal distribution Maximum likelihood Expectation–maximization algorithm Parameter Kalman filter Statistics Estimation theory M-estimators
210	Parameter-exploring Policy Gradients Frank Sehnkea , Christian Osendorfera , Thomas R¨ uckstießa , Alex Gravesa , Jan Petersc , J¨ urgen Schmidhubera,b a Add to Reading List Source URL: www6.in.tum.de Language: English - Date: 2013-05-15 08:23:49 Statistical theory Statistics M-estimators Econometrics Science Engineering Maximum likelihood Estimation theory Dimensional analysis Measurement

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