Statistical Learning and Data Sciences: Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings by Alexander GammermanStatistical Learning and Data Sciences: Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings by Alexander Gammerman

Statistical Learning and Data Sciences: Third International Symposium, SLDS 2015, Egham, UK, April…

byAlexander GammermanEditorVladimir Vovk, Harris Papadopoulos

Paperback | March 26, 2015

Pricing and Purchase Info

$92.97 online 
$110.50 list price save 15%
Earn 465 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015, held in Egham, Surrey, UK, April 2015.
The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on statistical learning and its applications, conformal prediction and its applications, new frontiers in data analysis for nuclear fusion, and geometric data analysis.
Title:Statistical Learning and Data Sciences: Third International Symposium, SLDS 2015, Egham, UK, April…Format:PaperbackDimensions:444 pages, 23.5 × 15.5 × 0.17 inPublished:March 26, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319170902

ISBN - 13:9783319170909

Look for similar items by category:

Reviews

Table of Contents

Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer.- Statistical Inference Problems and Their Rigorous Solutions.- Feature Mapping Through Maximization of the Atomic Interclass Distances.- Adaptive Design of Experiments for Sobol Indices Estimation Based on Quadratic Metamodel.- GoldenEye++: A Closer Look into the Black Box.- Gaussian Process Regression for Structured Data Sets.- Adaptive Design of Experiments Based on Gaussian Processes.- Forests of Randomized Shapelet Trees.- Aggregation of Adaptive Forecasting Algorithms Under Asymmetric Loss Function.- Visualization and Analysis of Multiple Time Series by Beanplot PCA.- Recursive SVM Based on TEDA.- RDE with Forgetting: An Approximate Solution for Large Values of k with an Application to Fault Detection Problems.- Sit-to-Stand Movement Recognition Using Kinect.- Additive Regularization of Topic Models for Topic Selection and Sparse Factorization.- Social Web-Based Anxiety Index's Predictive Information on S&P 500 Revisited.- Exploring the Link Between Gene Expression and Protein Binding by Integrating mRNA Microarray and ChIP-Seq Data.- Evolving Smart URL Filter in a Zone-Based Policy Firewall for Detecting Algorithmically Generated Malicious Domains.- Lattice-Theoretic Approach to Version Spaces in Qualitative Decision Making.- A Comparison of Three Implementations of Multi-Label Conformal Prediction.- Modifications to p-Values of Conformal Predictors.- Cross-Conformal Prediction with Ridge Regression.- Handling Small Calibration Sets in Mondrian Inductive Conformal Regressors.- Conformal Anomaly Detection of Trajectories with a Multi-class Hierarchy.- Model Selection Using Efficiency of Conformal Predictors.- Confidence Sets for Classification.- Conformal Clustering and Its Application to Botnet Traffic.- Interpretation of Conformal Prediction Classification Models.- New Frontiers in Data Analysis for Nuclear Fusion Confinement Regime Identification Using Artificial Intelligence Methods.- How to Handle Error Bars in Symbolic Regression for Data Mining in Scientific Applications.- Applying Forecasting to Fusion Databases.- Computationally Efficient Five-Class Image Classifier Based on Venn Predictors.- SOM and Feature Weights Based Method for Dimensionality Reduction in Large Gauss Linear Models.- Geometric Data Analysis Assigning Objects to Classes of a Euclidean Ascending Hierarchical Clustering.- The Structure of Argument: Semantic Mapping of US Supreme Court Cases.- Supporting Data Analytics for Smart Cities: An Overview of Data Models and Topology.- Manifold Learning in Regression Tasks.- Random Projection Towards the Baire Metric for High Dimensional Clustering.- Optimal Coding for Discrete Random Vector.