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020 _a9783540460565
_9978-3-540-46056-5
024 7 _a10.1007/11871842
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aMachine Learning: ECML 2006
_h[electronic resource] :
_b17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings /
_cedited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXXIII, 851 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v4212
505 0 _aInvited Talks -- On Temporal Evolution in Data Streams -- The Future of CiteSeer: CiteSeerx -- Learning to Have Fun -- Winning the DARPA Grand Challenge -- Challenges of Urban Sensing -- Long Papers -- Learning in One-Shot Strategic Form Games -- A Selective Sampling Strategy for Label Ranking -- Combinatorial Markov Random Fields -- Learning Stochastic Tree Edit Distance -- Pertinent Background Knowledge for Learning Protein Grammars -- Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies -- Sequence Discrimination Using Phase-Type Distributions -- Languages as Hyperplanes: Grammatical Inference with String Kernels -- Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning -- Fisher Kernels for Relational Data -- Evaluating Misclassifications in Imbalanced Data -- Improving Control-Knowledge Acquisition for Planning by Active Learning -- PAC-Learning of Markov Models with Hidden State -- A Discriminative Approach for the Retrieval of Imagesfrom Text Queries -- TildeCRF: Conditional Random Fields for Logical Sequences -- Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data -- Bayesian Learning of Markov Network Structure -- Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks -- Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions -- EM Algorithm for Symmetric Causal Independence Models -- Deconvolutive Clustering of Markov States -- Patching Approximate Solutions in Reinforcement Learning -- Fast Variational Inference for Gaussian Process Models Through KL-Correction -- Bandit Based Monte-Carlo Planning -- Bayesian Learning with Mixtures of Trees -- Transductive Gaussian Process Regression with Automatic Model Selection -- Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees -- Why Is Rule Learning Optimistic and How to Correct It -- Automatically Evolving Rule Induction Algorithms -- Bayesian Active Learning for Sensitivity Analysis -- Mixtures of Kikuchi Approximations -- Boosting in PN Spaces -- Prioritizing Point-Based POMDP Solvers -- Graph Based Semi-supervised Learning with Sharper Edges -- Margin-Based Active Learning for Structured Output Spaces -- Skill Acquisition Via Transfer Learning and Advice Taking -- Constant Rate Approximate Maximum Margin Algorithms -- Batch Classification with Applications in Computer Aided Diagnosis -- Improving the Ranking Performance of Decision Trees -- Multiple-Instance Learning Via Random Walk -- Localized Alternative Cluster Ensembles for Collaborative Structuring -- Distributional Features for Text Categorization -- Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data -- An Adaptive Kernel Method for Semi-supervised Clustering -- To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles -- Ensembles of Nearest Neighbor Forecasts -- Short Papers -- Learning Process Models with Missing Data -- Case-Based Label Ranking.-Cascade Evaluation of Clustering Algorithms -- Making Good Probability Estimates for Regression -- Fast Spectral Clustering of Data Using Sequential Matrix Compression -- An Information-Theoretic Framework for High-Order Co-clustering of Heterogeneous Objects -- Efficient Inference in Large Conditional Random Fields -- A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses -- Cost-Sensitive Decision Tree Learning for Forensic Classification -- The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces -- Right of Inference: Nearest Rectangle Learning Revisited -- Reinforcement Learning for MDPs with Constraints -- Efficient Non-linear Control Through Neuroevolution -- Efficient Prediction-Based Validation for Document Clustering -- On Testing the Missing at Random Assumption -- B-Matching for Spectral Clustering -- Multi-class Ensemble-Based Active Learning -- Active Learning with Irrelevant Examples.-Classification with Support Hyperplanes -- (Agnostic) PAC Learning Concepts in Higher-Order Logic -- Evaluating Feature Selection for SVMs in High Dimensions -- Revisiting Fisher Kernels for Document Similarities -- Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery -- Robust Probabilistic Calibration -- Missing Data in Kernel PCA -- Exploiting Extremely Rare Features in Text Categorization -- Efficient Large Scale Linear Programming Support Vector Machines -- An Efficient Approximation to Lookahead in Relational Learners -- Improvement of Systems Management Policies Using Hybrid Reinforcement Learning -- Diversified SVM Ensembles for Large Data Sets -- Dynamic Integration with Random Forests -- Bagging Using Statistical Queries -- Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption Test -- Spline Embedding for Nonlinear Dimensionality Reduction -- Cost-Sensitive Learning of SVM for Ranking -- Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures.
650 0 _aArtificial intelligence.
_93407
650 0 _aAlgorithms.
_93390
650 0 _aMachine theory.
_9163037
650 0 _aDatabase management.
_93157
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aAlgorithms.
_93390
650 2 4 _aFormal Languages and Automata Theory.
_9163038
650 2 4 _aDatabase Management.
_93157
700 1 _aFürnkranz, Johannes.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9163039
700 1 _aScheffer, Tobias.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9163040
700 1 _aSpiliopoulou, Myra.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9163041
710 2 _aSpringerLink (Online service)
_9163042
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540453758
776 0 8 _iPrinted edition:
_z9783540830719
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v4212
_9163043
856 4 0 _uhttps://doi.org/10.1007/11871842
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