http://www.eblida.org/activities/kic/survey-on-non-formal-informal-learningpublic-libraries-eu.html SURVEY ON NON-FORMAL AND INFORMAL LEARNING ACTIVITIES IN PUBLIC LIBRARIES ACROSS EUROPE PRŮZKUM NEFORMÁLNÍCH A INFO

Source URL: www.eblida.org

MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering. Albert Bifet1 , Geoff Holmes1 , Bernhard Pfahringer1 , Philipp Kranen2 , Hardy Kremer2 , Timm Jansen2 , and Thomas Seidl2 1

Source URL: moa.cs.waikato.ac.nz

• Data mining
• Statistics
• Computational statistics
• Software
• Machine learning
• Massive Online Analysis
• Cluster analysis
• Formal sciences
• Data stream mining
• K-means clustering
• Concept drift
• Weka

Decision Trees and Deep Networks for Pattern Classification Ananya Gupta University of Manchester Oxford Road, Manchester United Kingdom M13 9PL

Source URL: womencourage.acm.org

• Computational neuroscience
• Artificial neural networks
• Applied mathematics
• Cybernetics
• Cognitive science
• Formal sciences
• Artificial intelligence
• Convolutional neural network
• Deep learning
• MNIST database
• Machine learning
• Pattern recognition

J Educ Change:259–281 DOIs10833Informal learning organizations as part of an educational ecology: Lessons from collaboration across the formal-informal divide

Source URL: upclose.pitt.edu

• Education
• Educational psychology
• Euthenics
• Knowledge sharing
• Pedagogy
• Organizational behavior
• Collaboration
• Educational technology
• Informal learning
• Learning environment

Creedo—Scalable and Repeatable Extrinsic Evaluation for Pattern Discovery Systems by Online User Studies Mario Boley, Maike Krause-Traudes, Bo Kang and Björn Jacobs University of Bonn and Fraunhofer IAIS Schloss Birli

Source URL: poloclub.gatech.edu

• Formal sciences
• Academia
• Information technology
• Computing
• Data mining
• Business intelligence
• Usability
• Data management
• Evaluation
• Data analysis
• Association rule learning
• Pattern recognition

Online Learning for Big Data Analytics Irwin King, Michael R. Lyu and Haiqin Yang Department of Computer Science & Engineering The Chinese University of Hong Kong Tutorial presentation at IEEE Big Data, Santa Clara, CA,

Source URL: www.ischool.drexel.edu

• Computing
• Data
• Information technology
• Formal sciences
• Learning
• Business intelligence
• Big data
• Data management
• Transaction processing
• Machine learning
• Analytics
• Perceptron

The Threat of Algocracy: Reality, Resistance and Accommodation By John Danaher Forthcoming in Philosophy and Technology Abstract

Source URL: philpapers.org

• Cognitive science
• Academia
• Cybernetics
• Science and technology
• Formal sciences
• Algorithm
• Mathematical logic
• Theoretical computer science
• Big data
• Machine learning
• Legitimacy
• Artificial intelligence

A Comparison of Techniques for Selecting and Combining Class Association Rules Jan-Nikolas Sulzmann and Johannes F¨ urnkranz Department of Computer Science, TU Darmstadt Hochschulstr. 10, DDarmstadt, Germany

Source URL: www.ke.tu-darmstadt.de

• Data mining
• Association rule learning
• Data management
• Information science
• Information technology management
• Information
• Formal sciences
• Machine learning
• Statistical classification
• Confidence interval
• Sequential pattern mining
• Apriori algorithm

Grammatical Inference and Machine Learning Approaches to Post-Hoc LangSec Sheridan S. Curley Dr. Richard E. Harang

Source URL: spw16.langsec.org

• Formal languages
• Cognitive science
• Academia
• Cognition
• Language identification in the limit
• Grammar induction
• Recurrent neural network
• Algorithmic learning theory
• Context-free grammar
• Regular language
• Context-free language
• Formal grammar

Charu C. Aggarwal IBM T J Watson Research Center Yorktown, NYOutlier Ensembles

Source URL: www.outlier-analytics.org

• Statistics
• Information
• Data
• Data mining
• Robust statistics
• Outlier
• Statistical data
• Formal sciences
• Ensemble learning
• K-nearest neighbors algorithm
• Local outlier factor
• Anomaly detection