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Loss function
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#	Item
81	Local Rademacher Averages and Empirical Minimization Peter Bartlett Division of Computer Science and Department of Statistics UC Berkeley Joint work with Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2004-10-12 00:40:59 Machine learning Empirical risk minimization Loss function
82	INFORMS MATHEMATICS OF OPERATIONS RESEARCH Vol. 00, No. 0, Xxxxx 0000, pp. 000–000 issn 0364-765X \| eissn \| 00 \| 0000 \| 0001 Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-02-03 20:28:24 Statistics Statistical theory Estimation theory Bayesian statistics Statistical inference Stochastic simulation Loss function Bayes estimator Reinforcement learning Sampling Posterior probability Confidence interval
83	Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits Yasin Abbasi-Yadkori Dept. of Computing Science University of Alberta Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2012-02-08 11:48:18 Econometrics Machine learning Statistical theory Probability distributions Online machine learning Loss function Big O notation Sample complexity Confidence interval Normal distribution Matrix Algorithm
84	To sense or not-to-sense: Expression of Blumeria effector repertoires on barley loss-of-function mutant hosts Roger Wise Add to Reading List Source URL: emcrf.au.dk - Date: 2015-07-07 12:00:26
85	JMLR: Workshop and Conference Proceedings vol–26 24th Annual Conference on Learning Theory Regret Bounds for the Adaptive Control of Linear Quadratic Systems Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2011-09-04 20:45:19 Statistical theory Statistics Estimation theory Econometrics Loss function Economic lot scheduling problem
86	On Iterative Hard Thresholding Methods for High-dimensional M-Estimation Prateek Jain∗ Ambuj Tewari† Add to Reading List Source URL: dept.stat.lsa.umich.edu Language: English - Date: 2015-01-11 15:04:36 Statistics Statistical theory Estimation theory Sparse approximation Bias of an estimator Consistent estimator Loss function M-estimator Linear regression Sufficient statistic
87	ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models Sanjay Krishnan, Jiannan Wang, Eugene Wu † , Michael J. Franklin, Ken Goldberg UC Berkeley, † Columbia University {sanjaykrishnan, jnwang, fran Add to Reading List Source URL: sampleclean.org Language: English - Date: 2016-01-15 13:57:46 Statistics Statistical theory Estimator Statistical inference M-estimators Convex optimization Stochastic gradient descent Bias of an estimator Loss function Data analysis Linear regression Generalised Hough transform
88	Model selection Large scale model selection Summary and open problems Model Selection and Computational Oracle Inequalities for Large Scale Problems Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2012-07-10 18:14:07 Econometrics Statistical theory Regression analysis Estimation theory Linear regression Feature selection Model selection Support vector machine Loss function Oracle Database Natural selection Prediction
89	Bayesian Optimal Control of Smoothly Parameterized Systems: arXiv:1406.3926v1 [cs.LG] 16 Jun 2014 The Lazy Posterior Sampling Algorithm Yasin Abbasi-Yadkori Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-06-16 20:31:54 Statistics Statistical theory Econometrics Loss function Bayesian statistics Conjugate prior
90	Shift-Pessimistic Active Learning Using Robust Bias-Aware Prediction Anqi Liu Lev Reyzin Brian D. Ziebart Add to Reading List Source URL: www.levreyzin.com Language: English - Date: 2014-11-21 20:49:00 Machine learning Statistics Learning Estimation theory Statistical theory M-estimators Supervised learning Generalization error Cross entropy Maximum likelihood estimation Regression analysis Loss function

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