Solving Large Scale Learning Tasks. Challenges and Algorithms: Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday: Lecture Notes in Computer Science, cartea 9580
Editat de Stefan Michaelis, Nico Piatkowski, Marco Stolpeen Limba Engleză Paperback – 3 iul 2016
The 23 refereed articles in this Festschrift volume provide challenges and solutions from theoreticians and practitioners on data preprocessing, modeling, learning, and evaluation. Topics include data-mining and machine-learning algorithms, feature selection and feature generation, optimization as well as efficiency of energy and communication.
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Specificații
ISBN-13: 9783319417059
ISBN-10: 3319417053
Pagini: 377
Ilustrații: XIV, 387 p. 73 illus.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.56 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3319417053
Pagini: 377
Ilustrații: XIV, 387 p. 73 illus.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.56 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Online Social Networks Event Detection.- Detecting Events in Online Social Networks: Definitions, Trends and Challenges.- Why do we need data privacy.- Sharing Data with Guaranteed Privacy.- Distributed Support Vector Machines.- Big Data Classification — Aspects on Many Features.- Knowledge Discovery from Complex High Dimensional Data.- Local Pattern Detection in Attributed Graphs.- Advances in Exploratory Pattern Analytics on Ubiquitous Data and Social Media.- Understanding Human Mobility with Big Data.- On Event Detection from Spatial Time series for Urban Traffic Applications.- Compressible Reparametrization of Time-Variant Linear Dynamical Systems.- Detection of Local Intensity Changes in Grayscale Images with Robust Methods for Time-Series Analysis.- SCHEP — A Geometric Quality Measure for Regression Rule Sets, Gauging Ranking Consistency Throughout the Real-Valued Target Space.- Bayesian Ordinal Aggregation of Peer Assessments: A Case Study on KDD 2015.- Collaborative on linelearning of an action model.- Ontology-based Classification — Application of Machine Learning Concepts without Learning.- Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction.- Supervised Extraction of Usage Patterns in Different Document Representations.- Data-Driven Analyses of Electronic Text Books.- k-Morik: Mining Patterns to Classify Cartified Images of Katharina.
Caracteristici
Contains refereed papers dedicated to Katharina Morik and to her work Collects a number of papers by Prof. Morik's friends and collaborators over the years presenting a broad range of topics reflecting her versatility Adresses a large diversity of topics starting with natural language processing; machine learning, ranging from inductive logic programming to statistical learning; analysis of very large data collections; high-dimensional data; and resource awareness. Latest results include spatio-temporal random fields and integer Markov random fields, both allowing for complex probabilistic graphical models under resource constraints. Includes supplementary material: sn.pub/extras