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Produktbild: Machine Learning and Knowledge Discovery in Databases
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Machine Learning and Knowledge Discovery in Databases European Conference, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II

Aus der Reihe Lecture Notes in Artificial Intelligence
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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.09.2008

Abbildungen

XXIII, 698 p.

Herausgeber

Walter Daelemans + weitere

Verlag

Springer Berlin

Seitenzahl

698

Maße (L/B/H)

23,5/15,5/3,9 cm

Gewicht

1077 g

Auflage

2008

Sprache

Englisch

ISBN

978-3-540-87480-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.09.2008

Abbildungen

XXIII, 698 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

698

Maße (L/B/H)

23,5/15,5/3,9 cm

Gewicht

1077 g

Auflage

2008

Sprache

Englisch

ISBN

978-3-540-87480-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Machine Learning and Knowledge Discovery in Databases
  • Regular Papers.- Exceptional Model Mining.- A Joint Topic and Perspective Model for Ideological Discourse.- Effective Pruning Techniques for Mining Quasi-Cliques.- Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain.- Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs.- A New Natural Policy Gradient by Stationary Distribution Metric.- Towards Machine Learning of Grammars and Compilers of Programming Languages.- Improving Classification with Pairwise Constraints: A Margin-Based Approach.- Metric Learning: A Support Vector Approach.- Support Vector Machines, Data Reduction, and Approximate Kernel Matrices.- Mixed Bregman Clustering with Approximation Guarantees.- Hierarchical, Parameter-Free Community Discovery.- A Genetic Algorithm for Text Classification Rule Induction.- Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness.- Kernel-Based Inductive Transfer.- State-Dependent Exploration for Policy Gradient Methods.- Client-Friendly Classification over Random Hyperplane Hashes.- Large-Scale Clustering through Functional Embedding.- Clustering Distributed Sensor Data Streams.- A Novel Scalable and Data Efficient Feature Subset Selection Algorithm.- Robust Feature Selection Using Ensemble Feature Selection Techniques.- Effective Visualization of Information Diffusion Process over Complex Networks.- Actively Transfer Domain Knowledge.- A Unified View of Matrix Factorization Models.- Parallel Spectral Clustering.- Classification of Multi-labeled Data: A Generative Approach.- Pool-Based Agnostic Experiment Design in Linear Regression.- Distribution-Free Learning of Bayesian Network Structure.- Assessing Nonlinear Granger Causality from Multivariate Time Series.- Clustering Via Local Regression.- Decomposable Families of Itemsets.- Transferring Instances for Model-Based Reinforcement Learning.- A Simple Model for Sequences of Relational State Descriptions.- Semi-Supervised Boosting for Multi-Class Classification.- A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis.- Transferred Dimensionality Reduction.- Multiple Manifolds Learning Framework Based on Hierarchical Mixture Density Model.- Estimating Sales Opportunity Using Similarity-Based Methods.- Learning MDP Action Models Via Discrete Mixture Trees.- Continuous Time Bayesian Networks for Host Level Network Intrusion Detection.- Data Streaming with Affinity Propagation.- Semi-supervised Discriminant Analysis Via CCCP.- Demo Papers.- A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains.- Pleiades: Subspace Clustering and Evaluation.- SEDiL: Software for Edit Distance Learning.- Monitoring Patterns through an Integrated Management and Mining Tool.- A Knowledge-Based Digital Dashboard for Higher Learning Institutions.- SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model.