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Regression
Results: 13118

#	Item
101	Robust Sparse Regression under Adversarial Corruption Supplementary Material Yudong Chen Constantine Caramanis Add to Reading List Source URL: jmlr.org - Date: 2013-08-14 01:36:42
102	Model Learning with Local Gaussian Process Regression Duy Nguyen-Tuong Matthias Seeger Jan Peters Add to Reading List Source URL: www.ias.tu-darmstadt.de - Date: 2012-02-21 11:46:33
103	Gaussian Processes for Regression and Optimisation Phillip Boyle Submitted in fulfilment of the requirements Add to Reading List Source URL: homepages.mcs.vuw.ac.nz - Date: 2008-06-30 00:11:24
104	Genetic parameters for milk production and persistency in the Iranian Holstein population by the multitrait random regression model Add to Reading List Source URL: doi.fbn-dummerstorf.de - Date: 2014-08-05 05:14:03
105	Federalism-Facilitated Regulatory Innovation and Regression in a Time of Environmental Legislative Gridlock WILLIAM W. BUZBEE* ABSTRACT Despite a lengthy period of environmental legislative deadlock, the reach of Add to Reading List Source URL: gielr.files.wordpress.com - Date: 2016-06-06 20:43:59
106	Federalism-Facilitated Regulatory Innovation and Regression in a Time of Environmental Legislative Gridlock WILLIAM W. BUZBEE* ABSTRACT Despite a lengthy period of environmental legislative deadlock, the reach of Add to Reading List Source URL: perma-archives.org
107	Probabilistic Models for Classification: Logistic Regression Piyush Rai Machine Learning (CS771A) Aug 17, 2016 Add to Reading List Source URL: cse.iitk.ac.in - Date: 2016-09-08 06:05:58
108	Bayesian Non-parametric Simultaneous Quantile Regression for Complete and Grid Data Priyam Das∗ and Subhashis Ghosal † Add to Reading List Source URL: arxiv.org - Date: 2016-12-01 20:18:39
109	Adaptivity to Local Smoothness and Dimension in Kernel Regression Samory Kpotufe Toyota Technological Institute-Chicago∗ Add to Reading List Source URL: ttic.uchicago.edu - Date: 2013-12-30 13:33:12
110	Chapter 5 Multiple correlation and multiple regression The previous chapter considered how to determine the relationship between two variables and how to predict one from the other. The general solution was to consider Add to Reading List Source URL: www.personality-project.org - Date: 2010-09-18 09:53:06

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