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Loss function
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#	Item
41	A General Framework for Learning an Ensemble of Decision Rules Krzysztof Dembczyński1 , Wojciech Kotłowski1 , and Roman Słowiński1,2 1 2 Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Generalized functions Smooth functions Ensemble learning Gradient boosting Distribution Loss function Gradient descent Mathematical optimization Logarithm operator Dirac delta function
42	Budgeted Online Collective Inference Jay Pujara University of Maryland Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2015-07-31 17:33:33 Graphical models Statistical theory Probability theory Statistical models Bayesian inference Statistical inference Bayesian network Markov random field Belief propagation Scala First-order logic Loss function
43	Dynare Working Papers Series http://www.dynare.org/wp/ Indirect Likelihood Inference Michael Creel Add to Reading List Source URL: www.dynare.org Language: English - Date: 2011-07-11 10:23:40 Estimation theory Statistical theory Estimator Maximum likelihood estimation Bias of an estimator M-estimator Extremum estimator Generalized method of moments Bayes estimator Efficiency Asymptotic theory Loss function
44	Towards Optimal One Pass Large Scale Learning with Averaged Stochastic Gradient Descent Wei Xu Add to Reading List Source URL: arxiv.org Language: English - Date: 2011-12-22 22:14:38 Econometrics Estimation theory Statistical theory M-estimators Regression analysis Loss function Stochastic gradient descent Linear regression
45	Randomized Smoothing Techniques in Optimization Add to Reading List Source URL: stanford.edu Language: English - Date: 2014-10-16 22:22:19 Mathematical optimization Gradient descent Convex function Convex optimization Loss functions for classification
46	A Variational Analysis of Stochastic Gradient Algorithms Stephan Mandt , Matthew D. Hoffman , David M. Blei 1 2 Add to Reading List Source URL: www.stephanmandt.com Language: English - Date: 2016-06-23 13:49:43 Estimation theory Statistical theory Econometrics M-estimators Stochastic processes Loss function OrnsteinUhlenbeck process Stochastic gradient descent Likelihood function
47	Optimal Path Planning and Resource Allocation for Active Target Localization Charles Freundlich, Philippos Mordohai, and Michael M. Zavlanos Abstract— This paper addresses optimal path planning and resource allocation Add to Reading List Source URL: www.cs.stevens.edu Language: English - Date: 2015-04-28 19:49:30 Dynamic programming Markov processes Stochastic control Robot control Generalized functions Kalman filter Distribution Partially observable Markov decision process Markov decision process Loss function Covariance
48	Deviations from Core Prices and Income Inequality in the Arab World Rolando Gonzales Martinez (Bayesian Institute for Research on Development) Andrea Rojas-Hosse (Bayesian Institute for Research on Development) Add to Reading List Source URL: iariw.org Language: English - Date: 2015-11-12 17:25:10 Income distribution Economic inequality Welfare economics Distribution of wealth Summary statistics Gini coefficient Quantile regression Kuznets curve Inflation Economic growth Regression analysis Loss function
49	A General Framework for Learning an Ensemble of Decision Rules Krzysztof Dembczyński1 Wojciech Kotłowski1 Roman Słowiński1,2 Institute of Computing Science, Poznań University of Technology, Poznań, Poland Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Ensemble learning Gradient boosting Generalized functions Distribution Loss function Mathematical optimization Gradient descent Expected value Linear least squares Dirac delta function
50	Precision and Recall for Regression Luis Torgo1 and Rita Ribeiro2 1 2 Add to Reading List Source URL: www.dcc.fc.up.pt Language: English - Date: 2012-12-13 10:18:40 Econometrics Regression analysis Actuarial science Predictive analytics Prediction Normal distribution Time series Loss function Forecasting Linear regression