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Loss function
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#	Item
201	1 Chapter 5 Bayes Methods and Elementary Decision Theory 1. Elementary Decision Theory Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2010-02-24 17:55:21 Decision theory Bayesian statistics Econometrics Bayes estimator Loss function Conjugate prior Sufficient statistic Admissible decision rule Parametric model Statistics Statistical theory Estimation theory
202	A loss of FUS/TLS function leads to impaired cellular proliferation Add to Reading List Source URL: www.nature.com Language: English - Date: 2014-12-11 08:42:18 RNA interference Transcription factors Molecular genetics Gene expression FUS ERG Small interfering RNA Myc Carcinogenesis Biology Genetics RNA
203	Geometric and Topological Invariants of the Hypothesis Space Carlos C. Rodríguez Department of Mathematics and Statistics The University at Albany, SUNY. http://omega.albany.edu:8008/ Add to Reading List Source URL: omega.albany.edu Language: English - Date: 2010-09-01 16:13:58 Estimation theory Bayes estimator Conjugate prior Maximum likelihood Fisher information Loss function Empirical Bayes method Confidence interval Likelihood principle Statistics Bayesian statistics Statistical theory
204	20th International Congress on Modelling and Simulation, Adelaide, Australia, 1–6 December 2013 www.mssanz.org.au/modsim2013 An approach for developing and comparing empirical methods to model unaccounted losses in riv Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-11-19 22:14:19 Science Earth Environmental engineering Physical geography Scientific modeling Scientific modelling Runoff model Loss function Economic model Hydrology Water Hydraulic engineering
205	Information Theory Lecture 3: Applications to Machine Learning NU Logo Use Guidelines Mark Reid Add to Reading List Source URL: mark.reid.name Language: English - Date: 2015-03-10 00:10:59 Science Conditional entropy Entropy Loss function Mutual information Kullback–Leibler divergence Information theory Statistics Information
206	Statistics 582, Problem Set 4 Wellner; [removed]Reading: Lehmann, TPE, Chapter 5, sections 5.1 and 5.2. Course Notes, Chapter 5, sections 4-7. Due: Wednesday, February 4, 2015. Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-01-28 11:07:46 Maximum likelihood Minimax estimator Gamma distribution Conjugate prior Estimator Mean squared error Efficient estimator Loss function Statistics Estimation theory Bayes estimator
207	Statistics 582, Problem Set 3 Wellner; [removed]Reading: Handout on Huber’s Z−theorem, pages 1-10; Chapter 5, sections 1-4. Due: Wednesday, January 28, 2015. Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-01-21 12:10:44 Decision theory Bayes estimator Bayesian inference Loss function Spectral theory of ordinary differential equations Statistics Estimation theory Statistical theory
208	REPORTS expression is responsible for the cre1 ahk3 phenotype, because loss of AHP6 function in ahp6-1 cre1 ahk3 was able to suppress the ectopic protoxylem (91%; n[removed]Fig. 1B). In both wol and cre1 ahk2 ahk3, the AH Add to Reading List Source URL: www.marinespatialecologylab.org Language: English - Date: 2012-05-16 08:34:46 Fish Tropics Sparisoma Physical geography Parrotfish Stoplight parrotfish Exuma Cays Land and Sea Park Coral Queen parrotfish Scaridae Scarus Coral reefs
209	Loss Functions Robert C. Williamson Abstract Vapnik described the “three main learning problems” of pattern recognition, regression estimation and density estimation. These are defined in terms of the loss functions Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2013-04-06 02:21:38 Statistical theory Decision theory Kullback–Leibler divergence Thermodynamics Loss function Bregman divergence Bayes estimator Divergence Distribution Statistics Geometry Mathematical analysis
210	Learning for Stereo Vision Using the Structured Support Vector Machine Yunpeng Li Daniel P. Huttenlocher Department of Computer Science, Cornell University Ithaca, NY 14853 {yuli,dph}@cs.cornell.edu Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2008-07-27 07:57:45 Statistical inference Statistical classification Statistical models Loss function Parametric model Maximum likelihood Support vector machine Expectation–maximization algorithm Supervised learning Statistics Statistical theory Estimation theory

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