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Sampling theory
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51	Coreset and sampling approaches for the analysis of very large data sets – Part II Christian Sohler Prof. Dr. Christian Sohler Komplexitätstheorie und Add to Reading List Source URL: quentin.mrgt.fr Language: English - Date: 2014-01-09 09:41:45 Graph theory Graph NP-complete problems Graph coloring
52	Spectral Graph Theory Lecture 17 Sparsification by Effective Resistance Sampling Daniel A. Spielman Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2015-11-03 13:58:23 Linear algebra Chernoff bound Matrix Trace Exponentiation Random matrix
53	Minimizing Regret with Multiple Reserves TIM ROUGHGARDEN, Stanford University JOSHUA R. WANG, Stanford University We study the problem of computing and learning non-anonymous reserve prices to maximize revenue. We first Add to Reading List Source URL: web.stanford.edu Language: English - Date: 2016-08-08 16:20:04 Auction theory Mechanism design Auctions Game theory Vickrey auction VickreyClarkeGroves auction Auction VickreyClarkeGroves mechanism Matroid Linear programming Random-sampling mechanism
54	Auxiliary Gibbs Sampling for Inference in Piecewise-Constant Conditional Intensity Models Zhen Qin University of California, Riverside Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2015-05-14 15:51:40 Markov processes Graph theory Markov chain Gibbs sampling Probability distribution Bayesian network Resampling Sampling
55	IERI Academy January 17-21, 2011 Principles of Sampling, Item Response Theory and Proficiency Estimation Venue: National Institute of Education Nanyang Technological University Add to Reading List Source URL: ierinstitute.org Language: English - Date: 2012-01-05 08:16:08 Psychometrics Survey methodology Statistical models Sampling Item response theory Statistics
56	The descriptionâ€“experience gap in risky choice Add to Reading List Source URL: ie.technion.ac.il Language: English - Date: 2011-08-15 02:29:48 Decision theory Risk Actuarial science Utility Marketing Prospect theory Expected utility hypothesis Sampling Decision-making Cumulative prospect theory Choice Lottery
57	Knowing When You’re Wrong: Building Fast and Reliable Approximate Query Processing Systems Sameer Agarwal† , Henry Milner† , Ariel Kleiner† , Ameet Talwalkar† , Michael Jordan† , Samuel Madden‡ , Barzan Moz Add to Reading List Source URL: web.eecs.umich.edu Language: English - Date: 2015-03-27 17:54:39 Statistical inference Computational statistics Summary statistics Sampling Estimation theory Bootstrapping Resampling Confidence interval Statistics Sample size determination M-estimator Mode
58	2. Literature Review 2.1 The Concept of Hierarchical Models and Their Use in Educational Research Inevitably, individuals interact with their social contexts. Individuals’ characteristics can thus be influenced Add to Reading List Source URL: ierinstitute.org Language: English - Date: 2012-09-26 10:10:17 Sampling Statistical inference Measurement Estimation theory Error Multilevel model Linear regression Standard error Sample size determination Statistics Cluster sampling Errors and residuals
59	A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data Jiannan Wang, Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Tova Milo # , Tim Kraska † UC Berkeley, # Add to Reading List Source URL: www.cs.tau.ac.il Language: English - Date: 2014-05-12 10:21:00 Measurement Statistical theory Error Statistical inference Sampling Errors and residuals Statistics Confidence interval Outlier Bias of an estimator Sample size determination Statistical power
60	RANDOM FILTERS FOR COMPRESSIVE SAMPLING AND RECONSTRUCTION Joel A. Tropp,m Michael B. Wakin,r Marco F. Duarte,r Dror Baron,r and Richard G. Baraniuk r m r Department of Mathematics, The University of Michigan at Ann Arb Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2007-09-11 17:01:50 Digital signal processing Signal processing Filter theory Convolution Wavelet Filter Electronic filter Finite impulse response Compressed sensing Filter bank Compressed sensing in speech signals

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