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Loss function
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#	Item
221	Implicit Differentiation by Perturbation Justin Domke Rochester Institute of Technology [removed] Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2011-11-07 14:36:56 Estimation theory Probability theory Probability and statistics Decision theory Loss function Entropy Belief propagation Statistics Econometrics Statistical theory
222	Online Learning with Kernels Jyrki Kivinen Alex J. Smola Robert C. Williamson Research School of Information Sciences and Engineering Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 08:39:23 Statistical theory Computational statistics Neural networks Computational neuroscience Support vector machine Stochastic gradient descent Perceptron Loss function Robust statistics Statistics Machine learning Econometrics
223	Communication in Bargaining Over Decision Rights Wooyoung Lim ∗ Department of Economics Add to Reading List Source URL: ihome.ust.hk Language: English - Date: 2013-11-28 05:26:07 Estimation theory Decision theory Loss function Bargaining Dimensional analysis Statistics Statistical theory Econometrics
224	APPENDIX: Truncated Message Passing This appendix derives algorithm 2 from the main paper, which calculates the gradient of some loss function on the predicted marginals obtained after a fixed number of message-passing Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2011-11-07 14:36:56 Append Computing Games Ys
225	Conditional Random Fields for Multi-agent Reinforcement Learning Xinhua Zhang [removed] Douglas Aberdeen [removed] Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2009-06-21 14:46:49 Estimation theory Machine learning Conditional random field Theoretical computer science Reinforcement learning Loss function Markov decision process Rao–Blackwell theorem Bayesian network Statistics Graphical models Statistical theory
226	JMLR: Workshop and Conference Proceedings vol 35:1–31, 2014 Bayes-Optimal Scorers for Bipartite Ranking Aditya Krishna Menon ADITYA . MENON @ NICTA . COM . AU Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2014-02-24 02:00:41 Econometrics Loss function Statistical theory Function Supervised learning Statistics Mathematics Decision theory
227	Robust Bayesian Max-Margin Clustering Changyou Chen† Jun Zhu‡ Xinhua Zhang] † Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2014-10-30 20:29:12 Machine learning Statistical models Cluster analysis Mixture model Dirichlet process K-means clustering Variational Bayesian methods Loss function Hierarchical clustering Statistics Statistical theory Bayesian statistics
228	Learning for Optical Flow Using Stochastic Optimization Yunpeng Li and 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 07:54:40 Mathematics M-estimators Econometrics Simultaneous perturbation stochastic approximation Maximum likelihood Loss function Optical flow Supervised learning Motion estimation Statistics Estimation theory Statistical theory
229	Environmental policy under model uncertainty: a robust optimal control approach Michael Funke & Michael Paetz Add to Reading List Source URL: www.uni-hamburg.de Language: English - Date: 2013-04-10 04:57:23 Decision theory Environmental economics Economics of global warming Loss function Robustness Kullback–Leibler divergence Uncertainty Statistics Statistical theory Climate change policy
230	6.867 Machine learning, lecture 12 (Jaakkola) 1 Lecture topics: model selection criteria • Feature subset selection (cont’d) Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Estimation theory Statistical theory Information theory Naive Bayes classifier Mutual information Likelihood function Loss function Statistics Bayesian statistics Statistical classification

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