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Statistical learning theory
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#	Item
91	Learning Parameter Sets for Alignment Advising Dan DeBlasio John Kececioglu Department of Computer Science University of Arizona Add to Reading List Source URL: www.cs.arizona.edu Language: English - Date: 2015-03-06 18:58:58 Estimation theory Computational phylogenetics Bioinformatics Statistical theory Statistical inference Estimator Sequence alignment Multiple sequence alignment Parameter
92	A probabilistic approach to case-based inference Martin Anthony∗ Joel Ratsaby† Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2015-08-03 04:56:41 Machine learning Learning Case-based reasoning Critical thinking Inductive reasoning Reasoning Statistical learning theory Generalization error Expected value Equation solving
93	Learning stable, regularised latent models of neural population dynamics Lars Buesing, Jakob H. Macke and Maneesh Sahani Gatsby Computational Neuroscience Unit University College London, UK 17 Queen Square, London, WC1N Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:44 Estimation theory Regression analysis Statistical models Bayesian statistics Econometrics Maximum likelihood estimation Expectationmaximization algorithm Variational Bayesian methods Linear regression Autoregressive model Variance function Mixture model
94	Reproducibility is imperative for any scientific discovery. More often than not, modern scientific findings rely on statistical analysis of high-dimensional data. At a minimum, reproducibility manifests itself in stabili Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Machine learning Computational statistics Statistical models Statistical theory Statistical inference Bootstrapping Cross-validation Statistics Stability
95	Reject Options and Confidence Measures for kNN Classifiers∗ Christoph Dalitz Hochschule Niederrhein Fachbereich Elektrotechnik und Informatik Reinarzstr. 49, 47805 Krefeld, Germany Add to Reading List Source URL: lionel.kr.hs-niederrhein.de Language: English - Date: 2016-04-01 07:04:15 Statistical inference Estimation theory Machine learning Robust statistics K-nearest neighbors algorithm Statistical hypothesis testing Statistical classification Outlier Pattern recognition Estimator Bayes estimator Bootstrapping
96	Mathematical Modelling of Generalization Martin Anthony Department of Mathematics, London School of Economics Houghton Street, London WC2A 2AE, UK www.maths.lse.ac.uk/Personal/martin Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2002-09-24 16:32:03 Machine learning Statistical classification Computational learning theory Decision theory Rademacher complexity Stability VC dimension Support vector machine Sample complexity Generalization error VapnikChervonenkis theory
97	Learning Discriminative Fisher Kernels Laurens van der Maaten Pattern Recognition & Bio-informatics Laboratory, Delft University of Technology, THE NETHERLANDS Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Estimation theory Machine learning Statistical classification Fisher kernel Categorical data Pattern recognition Kernel method Positive-definite kernel Support vector machine Maximum likelihood estimation Kernel Likelihood function
98	EFFICIENT MONTE CARLO OPTIMIZATION FOR MULTI-LABEL CLASSIFIER CHAINS Jesse Read, Luca Martino∗ David Luengo∗ Dept. of Signal Theory and Communications Add to Reading List Source URL: perso.telecom-paristech.fr Language: English Machine learning Statistical classification Classifier chains Multi-label classification Pattern recognition Support vector machine Supervised learning Probabilistic classification Maximum a posteriori estimation Naive Bayes classifier Structured support vector machine
99	Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning Philip S. Thomas Dhruva Tirumala Emma Brunskill Carnegie Mellon University Add to Reading List Source URL: psthomas.com Language: English - Date: 2016-06-06 11:57:32 Estimation theory Statistical theory Statistical inference Robust statistics Least squares Estimator Bias of an estimator Efficiency Mean squared error L-estimator Consistent estimator Statistics
100	Nowcasting Events from the Social Web with Statistical Learning VASILEIOS LAMPOS and NELLO CRISTIANINI, University of Bristol, UK We present a general methodology for inferring the occurrence and magnitude of an event or Add to Reading List Source URL: www.lampos.net Language: English - Date: 2013-12-12 21:06:10 Machine learning Statistical methods Econometrics Model selection Estimation theory Feature selection Lasso Supervised learning Bootstrapping Pattern recognition Least squares Linear regression

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