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Statistical learning theory
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#	Item
381	5 Applied Machine Learning Theory 5-1 Monitoring and Analysis of Network Traffic in P2P Environment BAN Tao, ANDO Ruo, and KADOBAYASHI Youki Recent statistical studies on telecommunication networks outline that peer-to-p Add to Reading List Source URL: www.nict.go.jp Language: English - Date: 2013-11-21 20:23:58 Distributed computing Anonymous P2P Peer-to-peer Social peer-to-peer processes Winny HTTP Share Tor WASTE Computing Concurrent computing File sharing networks
382	Nuts and Bolts of Data Mining: Classifiers & ROC Curves By Tim Graettinger Yes or no. Buy or sell. Renew or cancel. Many customer behaviors have this flavor of a choice between two alternatives. Suppose software called a Add to Reading List Source URL: www.discoverycorpsinc.com Language: English - Date: 2012-02-16 18:17:45 Data mining Detection theory Receiver operating characteristic Socioeconomics Classifier Gain Predictive analytics Statistics Statistical classification Machine learning
383	Loss Functions Robert C. Williamson Abstract Vapnik described the “three main learning problems” of pattern recognition, regression estimation and density estimation. These are defined in terms of the loss functions Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2013-04-06 02:21:38 Statistical theory Decision theory Kullback–Leibler divergence Thermodynamics Loss function Bregman divergence Bayes estimator Divergence Distribution Statistics Geometry Mathematical analysis
384	Bayesian Online Learning for Multi-label and Multi-variate Performance Measures Xinhua Zhang University of Alberta [removed] Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2010-03-31 21:42:25 Support vector machine Supervised learning Sufficient statistic Bayes estimator Statistical classification Bayesian inference Kullback–Leibler divergence Mixture model Statistics Statistical theory Machine learning
385	Sample complexity of stochastic least squares system identi cation Erik Weyer1 Department of Chemical Engineering The University of Queensland Brisbane QLD 4072, Australia Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 04:24:05 Statistical classification VC dimension Statistics Computational learning theory Dimension
386	Learning for Stereo Vision Using the Structured Support Vector Machine Yunpeng Li 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 07:57:45 Statistical inference Statistical classification Statistical models Loss function Parametric model Maximum likelihood Support vector machine Expectation–maximization algorithm Supervised learning Statistics Statistical theory Estimation theory
387	JMLR: Workshop and Conference Proceedings vol[removed]–[removed]25th Annual Conference on Learning Theory Consistency of Nearest Neighbor Classification under Selective Sampling Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2012-06-17 06:50:55 Probability theory Independence Statistical dependence Nearest neighbor search Information science Mathematics Information retrieval
388	Journal of Machine Learning Research ? (2014) n–n + 48 Submitted 7/14; Published ? Composite Multiclass Losses Robert C. Williamson Australian National University & NICTA B OB .W ILLIAMSON @ ANU . EDU . AU Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2014-07-27 18:31:45 Statistical classification Statistical theory Scoring rule Bayes estimator Support vector machine Loss function Spectral theory of ordinary differential equations Statistics Decision theory Probability and statistics
389	2010 International Conference on Pattern Recognition The balanced accuracy and its posterior distribution Kay H. Brodersen∗† , Cheng Soon Ong∗ , Klaas E. Stephan† and Joachim M. Buhmann∗ ∗ Department † Ins Add to Reading List Source URL: www.ong-home.my Language: English - Date: 2013-12-12 02:50:01 Statistical theory Biostatistics Psychometrics Cross-validation Receiver operating characteristic Accuracy and precision Binary classification Confusion matrix Support vector machine Statistics Machine learning Statistical classification
390	Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms Xinhua Zhang∗ Statistical Machine Learning Program National ICT Australia, Canberra, Australia and CSL, RSISE, ANU, Canberra, Australia Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2009-06-21 14:46:52 Theoretical computer science Semi-supervised learning Supervised learning Graph Tree Flow network Active learning Graph theory Machine learning Mathematics

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