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Discovery Science [[electronic resource] ] : 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings / / edited by Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer
| Discovery Science [[electronic resource] ] : 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings / / edited by Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 |
| Descrizione fisica | 1 online resource (XVI, 404 p.) |
| Disciplina | 501 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Philosophy and science
Artificial intelligence Database management Information storage and retrieval Application software Philosophy of Science Artificial Intelligence Database Management Information Storage and Retrieval Computer Appl. in Administrative Data Processing Computer Appl. in Social and Behavioral Sciences |
| ISBN |
3-540-31698-1
3-540-29230-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Invention and Artificial Intelligence -- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources -- Training Support Vector Machines via SMO-Type Decomposition Methods -- The Robot Scientist Project -- The Arrowsmith Project: 2005 Status Report -- Regular Contributions - Long Papers -- Practical Algorithms for Pattern Based Linear Regression -- Named Entity Recognition for the Indonesian Language: Combining Contextual, Morphological and Part-of-Speech Features into a Knowledge Engineering Approach -- Bias Management of Bayesian Network Classifiers -- A Bare Bones Approach to Literature-Based Discovery: An Analysis of the Raynaud’s/Fish-Oil and Migraine-Magnesium Discoveries in Semantic Space -- Assisting Scientific Discovery with an Adaptive Problem Solver -- Cross-Language Mining for Acronyms and Their Completions from the Web -- Mining Frequent ?-Free Patterns in Large Databases -- An Experiment with Association Rules and Classification: Post-Bagging and Conviction -- Movement Analysis of Medaka (Oryzias Latipes) for an Insecticide Using Decision Tree -- Support Vector Inductive Logic Programming -- Measuring Over-Generalization in the Minimal Multiple Generalizations of Biosequences -- The q-Gram Distance for Ordered Unlabeled Trees -- Monotone Classification by Function Decomposition -- Learning On-Line Classification via Decorrelated LMS Algorithm: Application to Brain-Computer Interfaces -- An Algorithm for Mining Implicit Itemset Pairs Based on Differences of Correlations -- Pattern Classification via Single Spheres -- SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos -- Exploring Predicate-Argument Relations for Named Entity Recognition in the Molecular Biology Domain -- Massive Biomedical Term Discovery -- Active Constrained Clustering by Examining Spectral Eigenvectors -- Learning Ontology-Aware Classifiers -- Regular Contributions - Regular Papers -- Automatic Extraction of Proteins and Their Interactions from Biological Text -- A Data Analysis Approach for Evaluating the Behavior of Interestingness Measures -- Unit Volume Based Distributed Clustering Using Probabilistic Mixture Model -- Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search -- CLASSIC’CL: An Integrated ILP System -- Detecting and Revising Misclassifications Using ILP -- Project Reports -- Self-generation of Control Rules Using Hierarchical and Nonhierarchical Clustering for Coagulant Control of Water Treatment Plants -- A Semantic Enrichment of Data Tables Applied to Food Risk Assessment -- Knowledge Discovery Through Composited Visualization, Navigation and Retrieval -- A Tabu Clustering Method with DHB Operation and Mergence and Partition Operation -- Discovering User Preferences by Using Time Entries in Click-Through Data to Improve Search Engine Results -- Network Boosting for BCI Applications -- Rule-Based FCM: A Relational Mapping Model -- Effective Classifier Pruning with Rule Information -- Text Mining for Clinical Chinese Herbal Medical Knowledge Discovery. |
| Record Nr. | UNISA-996466222803316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Discovery science : 8th international conference, DS 2005, Singapore, October 8-11, 2005 : proceedings / / Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer (eds.)
| Discovery science : 8th international conference, DS 2005, Singapore, October 8-11, 2005 : proceedings / / Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer (eds.) |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2005 |
| Descrizione fisica | 1 online resource (XVI, 404 p.) |
| Disciplina | 501 |
| Altri autori (Persone) |
HoffmannAchim
MotodaHiroshi SchefferTobias |
| Collana | Lecture notes in computer science,Lecture notes in artificial intelligence |
| Soggetto topico |
Discoveries in science
Research - Data processing Science - Philosophy |
| ISBN |
3-540-31698-1
3-540-29230-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Invention and Artificial Intelligence -- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources -- Training Support Vector Machines via SMO-Type Decomposition Methods -- The Robot Scientist Project -- The Arrowsmith Project: 2005 Status Report -- Regular Contributions - Long Papers -- Practical Algorithms for Pattern Based Linear Regression -- Named Entity Recognition for the Indonesian Language: Combining Contextual, Morphological and Part-of-Speech Features into a Knowledge Engineering Approach -- Bias Management of Bayesian Network Classifiers -- A Bare Bones Approach to Literature-Based Discovery: An Analysis of the Raynaud’s/Fish-Oil and Migraine-Magnesium Discoveries in Semantic Space -- Assisting Scientific Discovery with an Adaptive Problem Solver -- Cross-Language Mining for Acronyms and Their Completions from the Web -- Mining Frequent ?-Free Patterns in Large Databases -- An Experiment with Association Rules and Classification: Post-Bagging and Conviction -- Movement Analysis of Medaka (Oryzias Latipes) for an Insecticide Using Decision Tree -- Support Vector Inductive Logic Programming -- Measuring Over-Generalization in the Minimal Multiple Generalizations of Biosequences -- The q-Gram Distance for Ordered Unlabeled Trees -- Monotone Classification by Function Decomposition -- Learning On-Line Classification via Decorrelated LMS Algorithm: Application to Brain-Computer Interfaces -- An Algorithm for Mining Implicit Itemset Pairs Based on Differences of Correlations -- Pattern Classification via Single Spheres -- SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos -- Exploring Predicate-Argument Relations for Named Entity Recognition in the Molecular Biology Domain -- Massive Biomedical Term Discovery -- Active Constrained Clustering by Examining Spectral Eigenvectors -- Learning Ontology-Aware Classifiers -- Regular Contributions - Regular Papers -- Automatic Extraction of Proteins and Their Interactions from Biological Text -- A Data Analysis Approach for Evaluating the Behavior of Interestingness Measures -- Unit Volume Based Distributed Clustering Using Probabilistic Mixture Model -- Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search -- CLASSIC’CL: An Integrated ILP System -- Detecting and Revising Misclassifications Using ILP -- Project Reports -- Self-generation of Control Rules Using Hierarchical and Nonhierarchical Clustering for Coagulant Control of Water Treatment Plants -- A Semantic Enrichment of Data Tables Applied to Food Risk Assessment -- Knowledge Discovery Through Composited Visualization, Navigation and Retrieval -- A Tabu Clustering Method with DHB Operation and Mergence and Partition Operation -- Discovering User Preferences by Using Time Entries in Click-Through Data to Improve Search Engine Results -- Network Boosting for BCI Applications -- Rule-Based FCM: A Relational Mapping Model -- Effective Classifier Pruning with Rule Information -- Text Mining for Clinical Chinese Herbal Medical Knowledge Discovery. |
| Altri titoli varianti | DS 2005 |
| Record Nr. | UNINA-9910484131603321 |
| Berlin ; ; New York, : Springer, c2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Knowledge discovery in databases : PKDD 2006 : 10th European Conference on Principle and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006 : proceedings / / Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (eds.)
| Knowledge discovery in databases : PKDD 2006 : 10th European Conference on Principle and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006 : proceedings / / Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (eds.) |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, 2006 |
| Descrizione fisica | 1 online resource (XXII, 660 p.) |
| Disciplina | 005.3/12 |
| Altri autori (Persone) |
FurnkranzJohannes
SchefferTobias SpiliopoulouMyra |
| Collana |
Lecture notes in computer science. Lecture notes in artificial intelligence
LNCS sublibrary. SL 7, Artificial intelligence |
| Soggetto topico |
Data mining
Database searching |
| ISBN | 3-540-46048-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited 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 -- SD-Map – A Fast Algorithm for Exhaustive Subgroup Discovery -- Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics -- Clustering Scientific Literature Using Sparse Citation Graph Analysis -- VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences -- Don’t Be Afraid of Simpler Patterns -- An Adaptive Prequential Learning Framework for Bayesian Network Classifiers -- Adaptive Active Classification of Cell Assay Images -- Learning Parameters in Entity Relationship Graphs from Ranking Preferences -- Detecting Fraudulent Personalities in Networks of Online Auctioneers -- Measuring Constraint-Set Utility for Partitional Clustering Algorithms -- Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering -- Optimal String Mining Under Frequency Constraints -- k-Anonymous Decision Tree Induction -- Closed Sets for Labeled Data -- Finding Trees from Unordered 0–1 Data -- Web Communities Identification from Random Walks -- Information Marginalization on Subgraphs -- Why Does Subsequence Time-Series Clustering Produce Sine Waves? -- Transductive Learning for Text Classification Using Explicit Knowledge Models -- Exploring Multiple Communities with Kernel-Based Link Analysis -- Distribution Rules with Numeric Attributes of Interest -- Tractable Models for Information Diffusion in Social Networks -- Efficient Spatial Classification Using Decoupled Conditional Random Fields -- Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data -- An Attacker’s View of Distance Preserving Maps for Privacy Preserving Data Mining -- A Scalable Distributed Stream Mining System for Highway Traffic Data -- K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance -- The Discrete Basis Problem -- Evaluation of Summarization Schemes for Learning in Streams -- Efficient Mining of Correlation Patterns in Spatial Point Data -- Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-Induced Subgraphs -- Refining Aggregate Conditions in Relational Learning -- Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification -- RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings -- Distributed Subgroup Mining -- Network Flow for Collaborative Ranking -- Short Papers -- Finding Hierarchies of Subspace Clusters -- Integrating Pattern Mining in Relational Databases -- Discovering Patterns in Real-Valued Time Series -- Classification of Dementia Types from Cognitive Profiles Data -- When Efficient Model Averaging Out-Performs Boosting and Bagging -- Peak-Jumping Frequent Itemset Mining Algorithms -- Autonomous Visualization -- Naive Bayes for Text Classification with Unbalanced Classes -- Knowledge-Conscious Data Clustering -- On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining -- Frequent Pattern Discovery Without Binarization: Mining Attribute Profiles -- Efficient Name Disambiguation for Large-Scale Databases -- Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures -- A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction -- Discovering Image-Text Associations for Cross-Media Web Information Fusion -- Mining Sequences of Temporal Intervals -- Pattern Teams -- Compression Picks Item Sets That Matter -- Discovering Overlapping Communities of Named Entities -- Closed Non-derivable Itemsets -- Learning a Distance Metric for Object Identification Without Human Supervision -- Towards Association Rules with Hidden Variables -- A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry -- Incremental Aspect Models for Mining Document Streams -- Learning Approximate MRFs from Large Transaction Data -- Similarity Search for Multi-dimensional NMR-Spectra of Natural Products. |
| Altri titoli varianti |
PKDD 2006
10th European Conference on Principles and Practice of Knowledge Discovery in Databases Tenth European Conference on Principles and Practice of Knowledge Discovery in Databases European Conference on Principles and Practice of Knowledge Discovery in Databases |
| Record Nr. | UNINA-9910768439003321 |
| Berlin ; ; New York, : Springer, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Knowledge Discovery in Databases: PKDD 2006 [[electronic resource] ] : 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings / / edited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou
| Knowledge Discovery in Databases: PKDD 2006 [[electronic resource] ] : 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings / / edited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (XXII, 660 p.) |
| Disciplina | 005.3/12 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data structures (Computer science)
Artificial intelligence Database management Information storage and retrieval Mathematical statistics Natural language processing (Computer science) Data Structures and Information Theory Artificial Intelligence Database Management Information Storage and Retrieval Probability and Statistics in Computer Science Natural Language Processing (NLP) |
| ISBN | 3-540-46048-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited 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 -- SD-Map – A Fast Algorithm for Exhaustive Subgroup Discovery -- Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics -- Clustering Scientific Literature Using Sparse Citation Graph Analysis -- VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences -- Don’t Be Afraid of Simpler Patterns -- An Adaptive Prequential Learning Framework for Bayesian Network Classifiers -- Adaptive Active Classification of Cell Assay Images -- Learning Parameters in Entity Relationship Graphs from Ranking Preferences -- Detecting Fraudulent Personalities in Networks of Online Auctioneers -- Measuring Constraint-Set Utility for Partitional Clustering Algorithms -- Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering -- Optimal String Mining Under Frequency Constraints -- k-Anonymous Decision Tree Induction -- Closed Sets for Labeled Data -- Finding Trees from Unordered 0–1 Data -- Web Communities Identification from Random Walks -- Information Marginalization on Subgraphs -- Why Does Subsequence Time-Series Clustering Produce Sine Waves? -- Transductive Learning for Text Classification Using Explicit Knowledge Models -- Exploring Multiple Communities with Kernel-Based Link Analysis -- Distribution Rules with Numeric Attributes of Interest -- Tractable Models for Information Diffusion in Social Networks -- Efficient Spatial Classification Using Decoupled Conditional Random Fields -- Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data -- An Attacker’s View of Distance Preserving Maps for Privacy Preserving Data Mining -- A Scalable Distributed Stream Mining System for Highway Traffic Data -- K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance -- The Discrete Basis Problem -- Evaluation of Summarization Schemes for Learning in Streams -- Efficient Mining of Correlation Patterns in Spatial Point Data -- Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-Induced Subgraphs -- Refining Aggregate Conditions in Relational Learning -- Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification -- RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings -- Distributed Subgroup Mining -- Network Flow for Collaborative Ranking -- Short Papers -- Finding Hierarchies of Subspace Clusters -- Integrating Pattern Mining in Relational Databases -- Discovering Patterns in Real-Valued Time Series -- Classification of Dementia Types from Cognitive Profiles Data -- When Efficient Model Averaging Out-Performs Boosting and Bagging -- Peak-Jumping Frequent Itemset Mining Algorithms -- Autonomous Visualization -- Naive Bayes for Text Classification with Unbalanced Classes -- Knowledge-Conscious Data Clustering -- On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining -- Frequent Pattern Discovery Without Binarization: Mining Attribute Profiles -- Efficient Name Disambiguation for Large-Scale Databases -- Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures -- A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction -- Discovering Image-Text Associations for Cross-Media Web Information Fusion -- Mining Sequences of Temporal Intervals -- Pattern Teams -- Compression Picks Item Sets That Matter -- Discovering Overlapping Communities of Named Entities -- Closed Non-derivable Itemsets -- Learning a Distance Metric for Object Identification Without Human Supervision -- Towards Association Rules with Hidden Variables -- A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry -- Incremental Aspect Models for Mining Document Streams -- Learning Approximate MRFs from Large Transaction Data -- Similarity Search for Multi-dimensional NMR-Spectra of Natural Products. |
| Record Nr. | UNISA-996466157203316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine learning : ECML 2006 : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006 : proceedings / / Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (eds.)
| Machine learning : ECML 2006 : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006 : proceedings / / Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (eds.) |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2006 |
| Descrizione fisica | 1 online resource (XXIII, 851 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) |
FurnkranzJohannes
SchefferTobias SpiliopoulouMyra |
| Collana |
Lecture notes in computer science. Lecture notes in artificial intelligence
LNCS sublibrary. SL 7, Artificial intelligence |
| Soggetto topico | Machine learning |
| ISBN | 3-540-46056-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited 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 Images from 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. |
| Altri titoli varianti |
ECML 2006
17th European Conference on Machine Learning Seventeenth European Conference on Machine Learning European Conference on Machine Learning |
| Record Nr. | UNINA-9910768437803321 |
| Berlin ; ; New York, : Springer, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning: ECML 2006 [[electronic resource] ] : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings / / edited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou
| Machine Learning: ECML 2006 [[electronic resource] ] : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings / / edited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (XXIII, 851 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Algorithms Mathematical logic Database management Artificial Intelligence Algorithm Analysis and Problem Complexity Mathematical Logic and Formal Languages Database Management |
| ISBN | 3-540-46056-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited 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 Images from 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. |
| Record Nr. | UNISA-996466136603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||