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Statistical learning theory
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#	Item
351	Large Scale Online Learning. L´eon Bottou NEC Labs America Princeton NJ[removed]removed] Add to Reading List Source URL: leon.bottou.org Language: English - Date: 2006-04-18 15:22:27 Analysis of algorithms Applied mathematics Statistical theory M-estimators Stochastic optimization Maximum likelihood Asymptotically optimal algorithm Fisher information Perceptron Statistics Estimation theory Mathematics
352	Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models Andr´e F.T. Martins3 , Manuele Bicego1,2, Vittorio Murino1,2 , Pedro M.Q. Aguiar4 , and M´ ario A.T. Figueiredo3 1 Add to Reading List Source URL: profs.sci.univr.it Language: English - Date: 2012-06-26 09:41:01 Category theory Fisher kernel Information retrieval Markov models Hidden Markov model Generative model Kernel Pattern recognition Discriminative model Statistics Machine learning Statistical classification
353	6.867 Machine learning, lecture 15 (Jaakkola) 1 Lecture topics: • Diﬀerent types of mixture models (cont’d) Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Statistical models Cluster analysis Expectation–maximization algorithm Missing data Mixture model Likelihood function Statistics Estimation theory Bayesian statistics
354	Signatures of Infinity: Nonergodicity and Resource Scaling in Prediction, Complexity, and Learning James P. Crutchfield Sarah Marzen Add to Reading List Source URL: www.santafe.edu Language: English - Date: 2015-04-03 15:58:21 Statistical theory Maximum likelihood Fisher information Entropy Divergence Markov chain Mutual information Likelihood function Parametric model Statistics Estimation theory Information theory
355	Mass Estimation and Its Applications ∗ Kai Ming Ting, Guang-Tong Zhou , Fei Tony Liu, James Tan Swee Chuan † Add to Reading List Source URL: www.cs.sfu.ca Language: English - Date: 2013-09-06 18:14:15 Statistical theory Estimation theory M-estimators Kernel density estimation Maximum likelihood Robust statistics Gaussian function Density estimation Normal distribution Statistics Non-parametric statistics Machine learning
356	LETTER Communicated by James Theiler Feature Selection via Coalitional Game Theory Shay Cohen Add to Reading List Source URL: www2.mta.ac.il Language: English - Date: 2010-06-22 06:48:22 Fair division Shapley value Statistical classification Feature selection Cooperative game Random forest Support vector machine Gain Stepwise regression Statistics Machine learning Game theory
357	6.867 Machine learning, lecture 16 (Jaakkola) 1 Lecture topics: • Mixture of Gaussians (cont’d) Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Statistical theory M-estimators Expectation–maximization algorithm Missing data Maximum likelihood Mixture model Conjugate prior Likelihood function Normal distribution Statistics Estimation theory Bayesian statistics
358	In 7th IEEE International Conference on Cybernetic Intelligent Systems, [removed]The Duality of Utility and Information in Optimally Learning Systems Roman V. Belavkin School of Computing Science Add to Reading List Source URL: www.eis.mdx.ac.uk Language: English - Date: 2008-10-03 05:45:44 Statistical theory Information theory Mathematics Probability theory Entropy Kullback–Leibler divergence Divergence Ordinal number Differential entropy Statistics Randomness Probability and statistics
359	6.867 Machine learning, lecture 10 (Jaakkola) 1 Lecture topics: model selection criteria • Structural risk minimization, example derivation Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Bayesian statistics Econometrics Bayesian inference Maximum likelihood Loss function Likelihood function Marginal likelihood Normal distribution Bayesian information criterion Statistics Estimation theory Statistical theory
360	The Discipline of Machine Learning Tom M. Mitchell July 2006 CMU-ML[removed] Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2006-07-05 19:35:50 Education Supervised learning Reinforcement learning E-learning Statistical classification Data mining Computational learning theory Speech recognition Genetic algorithm Machine learning Learning Artificial intelligence

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