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Statistical learning theory
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#	Item
181	Physica D–107 Data compression and learning in time sequences analysis A. Puglisi a,b,∗ , D. Benedetto c , E. Caglioti c , V. Loreto a,b , A. Vulpiani a,b a Add to Reading List Source URL: samarcanda.phys.uniroma1.it Language: English - Date: 2007-02-19 04:40:42 Mathematical analysis Randomness Statistical theory Thermodynamics Statistical randomness Entropy Random sequence Kullback–Leibler divergence Logarithm Statistics Probability and statistics Information theory
182	Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour Google Research and Tel Aviv Univ. Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2009-11-02 10:14:29 Machine learning Information theory Operator theory Kullback–Leibler divergence Thermodynamics Empirical risk minimization Entropy Hilbert space Multivariate normal distribution Statistics Statistical theory Probability and statistics
183	A Lazy Man’s Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration Peter Welinder‡ Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-11 10:56:51 Estimation theory Statistical classification Statistical inference Maximum likelihood Confidence interval Receiver operating characteristic Conjugate prior Gamma distribution Supervised learning Statistics Machine learning Biostatistics
184	Subgroup Discovery Meets Bayesian Networks—An Exceptional Model Mining Approach Add to Reading List Source URL: www.cs.uu.nl Language: English - Date: 2011-02-16 08:30:43 Graphical models Networks Bayesian network Group theory Machine learning Subgroup Statistics Bayesian statistics Statistical models
185	Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets Diederik P. Kingma Max Welling Machine Learning Group, University of Amsterdam Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-05-14 15:18:52 Statistical models Statistical theory Statistical inference Expectation–maximization algorithm Bayesian network Gibbs sampling Normal distribution Maximum likelihood Latent variable Statistics Bayesian statistics Estimation theory
186	Bayesian Learning via Stochastic Gradient Langevin Dynamics Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2011-05-21 11:48:52 Computational statistics Stochastic optimization Statistical mechanics Estimation theory Markov chain Monte Carlo Langevin dynamics Stochastic approximation Metropolis–Hastings algorithm Mixture model Statistics Probability and statistics Monte Carlo methods
187	On the Simultaneous Analysis of Clinical and Omics Data - a Comparison of Globalboosttest and Pre-validation Techniques Margret-Ruth Oelker and Anne-Laure Boulesteix Abstract In medical research biostatisticians are oft Add to Reading List Source URL: www.ibe.med.uni-muenchen.de Language: English - Date: 2012-08-18 19:00:07 Non-parametric statistics Machine learning Estimation theory Linear regression Resampling Cross-validation Intelligence quotient Statistical power Boosting Statistics Econometrics Regression analysis
188	Approximate Parameter Learning in Discriminative Fields Sanjiv Kumar and Martial Hebert The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.sanjivk.com Language: English - Date: 2010-06-01 18:50:54 M-estimators Econometrics Bayesian statistics Maximum likelihood Likelihood function Loss function Statistics Estimation theory Statistical theory
189	Monetary Policy Under Uncertainty and Learning Add to Reading List Source URL: larseosvensson.se Language: English - Date: 2013-07-17 18:49:46 Dynamic programming Equations Control theory Bellman equation Optimal design Loss function Macroeconomic model Statistics Statistical theory Mathematical optimization
190	Boosted Optimization for Network Classification Timothy Hancock Bioinformatics Center Institute for Chemical Research Kyoto University, Japan Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2010-03-31 18:50:22 Graph theory Ensemble learning Formal sciences Statistical models Belief propagation Gradient boosting AdaBoost Pattern recognition Bayesian network Statistics Graphical models Machine learning

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