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Linear model
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41	Adaptive Discriminative Generative Model and Its Applications † Ruei-Sung Lin† David Ross‡ Jongwoo Lim† Ming-Hsuan Yang∗ University of Illinois ‡ University of Toronto ∗ Honda Research Institute Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2005-01-07 15:34:20 Statistics Probability Mathematical analysis Statistical models Machine learning Markov models Linear algebra Multivariate statistics Discriminative model Kalman filter Generative model Normal distribution
42	Course Algebraic Modelling MTHSecondary Cycle One Add to Reading List Source URL: www.carrefourfga.com Language: English - Date: 2014-03-24 10:29:59 Mathematics Algebra Academia Equation Emmy Noether Economic model Elementary algebra Logarithm Geometry Algebraic geometry Linear algebraic group
43	Gaussian sampling by local perturbations George Papandreou Department of Statistics University of California, Los Angeles Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2010-10-31 18:18:15 Statistics Statistical models Stochastic processes Linear filters Bayesian statistics Estimation theory Gibbs sampling Normal distribution Kalman filter Mixture model Bayesian network Gaussian process
44	RMM Vol. 2, 2011, 146–178 Special Topic: Statistical Science and Philosophy of Science Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/ Aris Spanos Add to Reading List Source URL: www.rmm-journal.com Language: English - Date: 2011-10-27 11:24:50 Statistics Statistical theory Psychometrics Hypothesis testing Abduction Deductive reasoning Statistical inference Confidence interval Linear regression Statistical model Statistical hypothesis testing Frequentist probability
45	LINEAR ALGEBRA: BEWARE! MATH 196, SECTION 57 (VIPUL NAIK) You might be expecting linear algebra to be a lot like your calculus classes at the University. This is probably true in terms of the course structure and format. Add to Reading List Source URL: files.vipulnaik.com Language: English - Date: 2016-08-13 11:33:29 Mathematics Mathematical analysis Elementary algebra Equations Functions and mappings Linear equation Linear algebra Linear function Mathematical model Linearity Parameter Function
46	Groups in stable and simple theories Dugald Macpherson, School of Mathematics, University of Leeds, Leeds LS2 9JT,UK April 7, 2010 These are sketch notes for my lecture on the MALOA Introductory Day Add to Reading List Source URL: www1.maths.leeds.ac.uk Language: English - Date: 2010-08-16 05:13:00 Algebra Group theory Abstract algebra Model theory Stable group Morley rank Stable theory Linear algebraic group Algebraic group Abelian group FeitThompson theorem Structure
47	Chapter 5 Local Regress ion Trees In this chapter we explore the hypothesis of improving the accuracy of regression trees by using smoother models at the tree leaves. Our proposal consists of using local regression model Add to Reading List Source URL: www.dcc.fc.up.pt Language: English - Date: 2012-12-13 10:18:43 Regression analysis Statistics Estimation theory Nonparametric statistics Parametric statistics Polynomial regression Local regression Decision tree learning Kernel regression Ordinary least squares Nonparametric regression Linear regression
48	INFERENCE IN HIGH DIMENSIONAL PANEL MODELS WITH AN APPLICATION TO GUN CONTROL arXiv:1411.6507v1 [stat.ME] 24 NovALEXANDRE BELLONI, VICTOR CHERNOZHUKOV, CHRISTIAN HANSEN, AND DAMIAN KOZBUR Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-11-24 20:40:16 Statistics Regression analysis Estimation theory Lasso Linear regression Random effects model Least squares Fixed effects model Ordinary least squares Instrumental variable Feature selection Heteroscedasticity
49	Evaluating Interval-Valued Influence DiagramsI Rafael Caba˜nasa,∗, Alessandro Antonuccib , Andr´es Canoa , Manuel G´omez-Olmedoa a Department of Computer Science and Artificial Intelligence CITIC, University of Gran Add to Reading List Source URL: ipg.idsia.ch Language: English - Date: 2016-05-24 15:35:25 Mathematics Logic Model theory Abstraction Limit Interpretation IP Bayesian network Static single assignment form Symbol Expected value Linear temporal logic
50	Simultaneous Learning of Motion and Sensor Model Parameters for Mobile Robots Teddy N. Yap, Jr. and Christian R. Shelton Department of Computer Science and Engineering University of California, Riverside, CA 92521, USA { Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:14 Robot control Statistics Robot navigation Estimation theory Engineering Artificial intelligence Linear filters Simultaneous localization and mapping Monte Carlo methods Kalman filter Robot calibration Sensor

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