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978-3-642-15939-8 |
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20221012204032.0 |
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100818s2010 gw | s |||| 0|eng d |
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|a 9783642159398
|9 978-3-642-15939-8
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|a 10.1007/978-3-642-15939-8
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|a Machine Learning and Knowledge Discovery in Databases
|h [electronic resource] :
|b European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part III /
|c edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag.
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| 250 |
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|a 1st ed. 2010.
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| 264 |
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1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2010.
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| 300 |
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|a XXII, 632 p. 183 illus.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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| 347 |
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|a text file
|b PDF
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| 490 |
1 |
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|a Lecture Notes in Artificial Intelligence,
|x 2945-9141 ;
|v 6323
|
| 505 |
0 |
|
|a Regular Papers -- Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations -- Unsupervised Trajectory Sampling -- Fast Extraction of Locally Optimal Patterns Based on Consistent Pattern Function Variations -- Large Margin Learning of Bayesian Classifiers Based on Gaussian Mixture Models -- Learning with Ensembles of Randomized Trees : New Insights -- Entropy and Margin Maximization for Structured Output Learning -- Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms -- Adapting Decision DAGs for Multipartite Ranking -- Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs -- Modeling Relations and Their Mentions without Labeled Text -- An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery -- Selecting Information Diffusion Models over Social Networks for Behavioral Analysis -- Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach -- Online Structural Graph Clustering Using Frequent Subgraph Mining -- Large-Scale Support Vector Learning with Structural Kernels -- Synchronization Based Outlier Detection -- Laplacian Spectrum Learning -- k-Version-Space Multi-class Classification Based on k-Consistency Tests -- Complexity Bounds for Batch Active Learning in Classification -- Semi-supervised Projection Clustering with Transferred Centroid Regularization -- Permutation Testing Improves Bayesian Network Learning -- Example-dependent Basis Vector Selection for Kernel-Based Classifiers -- Surprising Patterns for the Call Duration Distribution of Mobile Phone Users -- Variational Bayesian Mixture of Robust CCA Models -- Adverse Drug Reaction Mining in Pharmacovigilance Data Using Formal Concept Analysis -- Topic Models Conditioned on Relations -- Shift-Invariant Grouped Multi-task Learning for Gaussian Processes -- Nonparametric Bayesian Clustering Ensembles -- Directed Graph Learning via High-Order Co-linkage Analysis -- Incorporating Domain Models into Bayesian Optimization for RL -- Efficient and Numerically Stable Sparse Learning -- Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes -- Many-to-Many Graph Matching: A Continuous Relaxation Approach -- Competitive Online Generalized Linear Regression under Square Loss -- Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning -- Fast, Effective Molecular Feature Mining by Local Optimization -- Demo Papers -- AnswerArt - Contextualized Question Answering -- Real-Time News Recommender System -- CET: A Tool for Creative Exploration of Graphs -- NewsGist: A Multilingual Statistical News Summarizer -- QUEST: Query Expansion Using Synonyms over Time -- Flu Detector - Tracking Epidemics on Twitter -- X-SDR: An Extensible Experimentation Suite for Dimensionality Reduction -- SOREX: Subspace Outlier Ranking Exploration Toolkit -- KDTA: Automated Knowledge-Driven Text Annotation -- Detecting Events in a Million New York Times Articles -- Experience STORIES: A Visual News Search and Summarization System -- Exploring Real Mobility Data with M-Atlas.
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| 650 |
|
0 |
|a Artificial intelligence.
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| 650 |
|
0 |
|a Data structures (Computer science).
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| 650 |
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0 |
|a Information theory.
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| 650 |
|
0 |
|a Application software.
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| 650 |
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0 |
|a Information storage and retrieval systems.
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| 650 |
|
0 |
|a Database management.
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| 650 |
|
0 |
|a Data mining.
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| 650 |
1 |
4 |
|a Artificial Intelligence.
|
| 650 |
2 |
4 |
|a Data Structures and Information Theory.
|
| 650 |
2 |
4 |
|a Computer and Information Systems Applications.
|
| 650 |
2 |
4 |
|a Information Storage and Retrieval.
|
| 650 |
2 |
4 |
|a Database Management.
|
| 650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
|
| 700 |
1 |
|
|a Balcázar, José L.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 700 |
1 |
|
|a Bonchi, Francesco.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
|
|a Gionis, Aristides.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 700 |
1 |
|
|a Sebag, Michèle.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 710 |
2 |
|
|a SpringerLink (Online service)
|
| 773 |
0 |
|
|t Springer Nature eBook
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783642159381
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783642159404
|
| 830 |
|
0 |
|a Lecture Notes in Artificial Intelligence,
|x 2945-9141 ;
|v 6323
|
| 856 |
4 |
0 |
|u https://doi.uam.elogim.com/10.1007/978-3-642-15939-8
|z Texto Completo
|
| 912 |
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|a ZDB-2-SCS
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| 912 |
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|a ZDB-2-SXCS
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| 912 |
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|a ZDB-2-LNC
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| 950 |
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|a Computer Science (SpringerNature-11645)
|
| 950 |
|
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|a Computer Science (R0) (SpringerNature-43710)
|
