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Supervised learning
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#	Item
431	LEARNING FROM DATA WITH COMPLEX INTERACTIONS AND AMBIGUOUS LABELS By Soumya Ray Add to Reading List Source URL: pages.cs.wisc.edu Language: English - Date: 2005-12-16 17:20:16 Econometrics Mathematics Cybernetics Supervised learning Algorithm Regression analysis Synthetic data Statistics Machine learning Applied mathematics
432	A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data Do-kyum Kim, Matthew Der and Lawrence K. Saul Department of Computer Science and Engineering, University of California, San D Add to Reading List Source URL: cseweb.ucsd.edu Language: English Estimation theory Learning Statistical theory Semi-supervised learning Expectation–maximization algorithm Supervised learning Support vector machine Maximum likelihood Stability Statistics Machine learning Statistical classification
433	arXiv:1112.6209v5 [cs.LG] 12 JulBuilding High-level Features Using Large Scale Unsupervised Learning Quoc V. Le Add to Reading List Source URL: arxiv.org Language: English - Date: 2012-07-12 20:39:43 Computational statistics Neural network Pattern recognition Supervised learning Unsupervised learning Caltech 101 Machine learning Artificial intelligence Learning
434	5.7 Additional File 7: Validation Use Case Examples We describe here three example validation Use Cases for application to predictive toxicology modelsValidate a Prediction Model The user who wants to evaluate a Add to Reading List Source URL: jcheminf.com Language: English Science Pharmaceutical industry Quality Validation Validity Training set Algorithm Learning Supervised learning Machine learning Statistics Theoretical computer science
435	WSC' 03 Sample Paper Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 21:55:07 Machine learning Science Mind Artificial neural network Classical conditioning Supervised learning Perceptron Generalized Hebbian Algorithm Unsupervised learning Neural networks Computational neuroscience Cybernetics
436	Joint Deep Learning for Pedestrian Detection Wanli Ouyang and Xiaogang Wang Department of Electronic Engineering, the Chinese University of Hong Kong wlouyang, Abstract Add to Reading List Source URL: www.ee.cuhk.edu.hk Language: English - Date: 2013-10-15 09:27:14 Solid mechanics Materials science Computer vision Image processing Pedestrian detection Surveillance Supervised learning Hough transform Linear classifier Mechanics Physics Deformation
437	LNCSEvaluating Query-Independent Object Features for Relevancy Prediction Add to Reading List Source URL: www.dcs.gla.ac.uk Language: English - Date: 2008-01-05 04:43:23 Bayesian statistics Statistical classification Machine learning Natural language processing Relevance feedback Naive Bayes classifier Supervised learning Feature selection Training set Statistics Information science Information retrieval
438	Convex Modeling with Priors by Benjamin Recht B.S., University of ChicagoM.S., Massachusetts Institute of Technology (2002) Add to Reading List Source URL: www.cba.mit.edu Language: English - Date: 2011-12-13 18:32:07 Mathematical optimization Regression analysis Image processing Nonlinear dimensionality reduction Supervised learning Neil Gershenfeld Segmentation Cluster analysis Spectral clustering Statistics Machine learning Multivariate statistics
439	arXiv:1302.4922v4 [stat.ML] 13 MayStructure Discovery in Nonparametric Regression through Compositional Kernel Search David Duvenaud∗† Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-05-13 20:11:41 Nonparametric regression Kernel Support vector machine Semiparametric regression Supervised learning Additive model Shogun Bayesian additive regression kernels Statistics Non-parametric statistics Regression analysis
440	IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 1 Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems Add to Reading List Source URL: www.genetic-programming.org Language: English - Date: 2013-06-23 23:44:56 Learning Learning classifier system Statistical classification Genetic algorithm Classifier Supervised learning Reinforcement learning Binary classification Machine learning Statistics Artificial intelligence

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