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Home > Machine Learning: ECML 2005: 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings > Learning Models of Relational Stochastic Processes
Machine Learning: ECML 2005: 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings |
João Gama; Rui Camacho; Pavel Brazdil; Alípio Jorge; Luís Torgo
Springer Berlin Heidelberg
Machine Learning: ECML 2005: 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings
Learning Models of Relational Stochastic Processes
Authors

Sumit Sanghai; Pedro Domingos; Daniel Weld

ARI Id

1664841803432_3740697

Access

Not Available Free

Pages

715-723

DOI

10.1007/11564096_73

Chapter URL

https://rd.springer.com/chapter/10.1007/11564096_73

Table of Contents of Book
Showing 1 to 20 of 80 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
Data Analysis in the Life Sciences — Sparking Ideas —
Michael R. Berthold
1-1
Machine Learning for Natural Language Processing (and Vice Versa?)
Claire Cardie
2-2
Statistical Relational Learning: An Inductive Logic Programming Perspective
Luc De Raedt
3-5
Recent Advances in Mining Time Series Data
Eamonn Keogh
6-6
Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce
Ron Kohavi
7-7
Data Streams and Data Synopses for Massive Data Sets (Invited Talk)
Yossi Matias
8-9
Clustering and Metaclustering with Nonnegative Matrix Decompositions
Liviu Badea
10-22
A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems
Christian Bessiere; Remi Coletta; Frédéric Koriche; Barry O’Sullivan
23-34
Estimation of Mixture Models Using Co-EM
Steffen Bickel; Tobias Scheffer
35-46
Nonrigid Embeddings for Dimensionality Reduction
Matthew Brand
47-59
Multi-view Discriminative Sequential Learning
Ulf Brefeld; Christoph Büscher; Tobias Scheffer
60-71
Robust Bayesian Linear Classifier Ensembles
Jesús Cerquides; Ramon López de Mántaras
72-83
An Integrated Approach to Learning Bayesian Networks of Rules
Jesse Davis; Elizabeth Burnside; Inês de Castro Dutra; David Page; Vítor Santos Costa
84-95
Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam
Isabel Drost; Tobias Scheffer
96-107
Rotational Prior Knowledge for SVMs
Arkady Epshteyn; Gerald DeJong
108-119
On the LearnAbility of Abstraction Theories from Observations for Relational Learning
Stefano Ferilli; Teresa M. A. Basile; Nicola Di Mauro; Floriana Esposito
120-132
Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers
George Forman; Ira Cohen
133-145
Kernel Basis Pursuit
Vincent Guigue; Alain Rakotomamonjy; Stéphane Canu
146-157
Hybrid Algorithms with Instance-Based Classification
Iris Hendrickx; Antal van den Bosch
158-169
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 80 entries
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