Machine learning and knowledge discovery in databases [[electronic resource] ] : European conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009 : proceedings . Part I / / Wray Buntin, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor (eds.) |
Edizione | [1st ed. 2009.] |
Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2009 |
Descrizione fisica | 1 online resource (XXIX, 756 p.) |
Disciplina | 006.3/12 |
Altri autori (Persone) |
BuntineWray
GrobelnikMarko MladenicDunja <1967-> Shawe-TaylorJohn |
Collana | Lecture notes in computer science |
Soggetto topico |
Machine learning
Data mining Database searching |
ISBN | 3-642-04180-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Invited Talks (Abstracts) -- Theory-Practice Interplay in Machine Learning – Emerging Theoretical Challenges -- Are We There Yet? -- The Growing Semantic Web -- Privacy in Web Search Query Log Mining -- Highly Multilingual News Analysis Applications -- Machine Learning Journal Abstracts -- Combining Instance-Based Learning and Logistic Regression for Multilabel Classification -- On Structured Output Training: Hard Cases and an Efficient Alternative -- Sparse Kernel SVMs via Cutting-Plane Training -- Hybrid Least-Squares Algorithms for Approximate Policy Evaluation -- A Self-training Approach to Cost Sensitive Uncertainty Sampling -- Learning Multi-linear Representations of Distributions for Efficient Inference -- Cost-Sensitive Learning Based on Bregman Divergences -- Data Mining and Knowledge Discovery Journal Abstracts -- RTG: A Recursive Realistic Graph Generator Using Random Typing -- Taxonomy-Driven Lumping for Sequence Mining -- On Subgroup Discovery in Numerical Domains -- Harnessing the Strengths of Anytime Algorithms for Constant Data Streams -- Identifying the Components -- Two-Way Analysis of High-Dimensional Collinear Data -- A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process -- Regular Papers -- Evaluation Measures for Multi-class Subgroup Discovery -- Empirical Study of Relational Learning Algorithms in the Phase Transition Framework -- Topic Significance Ranking of LDA Generative Models -- Communication-Efficient Classification in P2P Networks -- A Generalization of Forward-Backward Algorithm -- Mining Graph Evolution Rules -- Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks -- Adaptive XML Tree Classification on Evolving Data Streams -- A Condensed Representation of Itemsets for Analyzing Their Evolution over Time -- Non-redundant Subgroup Discovery Using a Closure System -- PLSI: The True Fisher Kernel and beyond -- Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization -- One Graph Is Worth a Thousand Logs: Uncovering Hidden Structures in Massive System Event Logs -- Conference Mining via Generalized Topic Modeling -- Within-Network Classification Using Local Structure Similarity -- Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC) -- Kernel Polytope Faces Pursuit -- Soft Margin Trees -- Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs -- Margin and Radius Based Multiple Kernel Learning -- Inference and Validation of Networks -- Binary Decomposition Methods for Multipartite Ranking -- Leveraging Higher Order Dependencies between Features for Text Classification -- Syntactic Structural Kernels for Natural Language Interfaces to Databases -- Active and Semi-supervised Data Domain Description -- A Matrix Factorization Approach for Integrating Multiple Data Views -- Transductive Classification via Dual Regularization -- Stable and Accurate Feature Selection -- Efficient Sample Reuse in EM-Based Policy Search -- Applying Electromagnetic Field Theory Concepts to Clustering with Constraints -- An ?1 Regularization Framework for Optimal Rule Combination -- A Generic Approach to Topic Models -- Feature Selection by Transfer Learning with Linear Regularized Models -- Integrating Logical Reasoning and Probabilistic Chain Graphs -- Max-Margin Weight Learning for Markov Logic Networks -- Parameter-Free Hierarchical Co-clustering by n-Ary Splits -- Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts -- Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks -- Kernel-Based Copula Processes -- Compositional Models for Reinforcement Learning -- Feature Selection for Value Function Approximation Using Bayesian Model Selection -- Learning Preferences with Hidden Common Cause Relations -- Feature Selection for Density Level-Sets -- Efficient Multi-start Strategies for Local Search Algorithms -- Considering Unseen States as Impossible in Factored Reinforcement Learning -- Relevance Grounding for Planning in Relational Domains. |
Altri titoli varianti | ECML PKDD 2009 |
Record Nr. | UNINA-9910483698603321 |
Berlin ; ; New York, : Springer, c2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Machine learning and knowledge discovery in databases [[electronic resource] ] : European conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009 : proceedings . Part II / / Wray Buntin, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor (eds.) |
Edizione | [1st ed. 2009.] |
Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2009 |
Descrizione fisica | 1 online resource (XXIX, 762 p.) |
Disciplina | 004.6 |
Altri autori (Persone) |
BuntineWray
GrobelnikMarko MladenicDunja <1967-> Shawe-TaylorJohn |
Collana | Lecture notes in computer science |
Soggetto topico |
Machine learning
Data mining Database searching |
ISBN | 3-642-04174-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Regular Papers -- Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines -- A Convex Method for Locating Regions of Interest with Multi-instance Learning -- Active Learning for Reward Estimation in Inverse Reinforcement Learning -- Simulated Iterative Classification A New Learning Procedure for Graph Labeling -- Graph-Based Discrete Differential Geometry for Critical Instance Filtering -- Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams -- Neural Networks for State Evaluation in General Game Playing -- Learning to Disambiguate Search Queries from Short Sessions -- Dynamic Factor Graphs for Time Series Modeling -- On Feature Selection, Bias-Variance, and Bagging -- Efficient Pruning Schemes for Distance-Based Outlier Detection -- The Sensitivity of Latent Dirichlet Allocation for Information Retrieval -- Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification -- The Model of Most Informative Patterns and Its Application to Knowledge Extraction from Graph Databases -- On Discriminative Parameter Learning of Bayesian Network Classifiers -- Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint -- Classifier Chains for Multi-label Classification -- Dependency Tree Kernels for Relation Extraction from Natural Language Text -- Statistical Relational Learning with Formal Ontologies -- Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm -- Capacity Control for Partially Ordered Feature Sets -- Reconstructing Data Perturbed by Random Projections When the Mixing Matrix Is Known -- Identifying the Original Contribution of a Document via Language Modeling -- Relaxed Transfer of Different Classes via Spectral Partition -- Mining Databases to Mine Queries Faster -- MACs: Multi-Attribute Co-clusters with High Correlation Information -- Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs -- Latent Dirichlet Allocation for Automatic Document Categorization -- New Regularized Algorithms for Transductive Learning -- Enhancing the Performance of Centroid Classifier by ECOC and Model Refinement -- Optimal Online Learning Procedures for Model-Free Policy Evaluation -- Kernels for Periodic Time Series Arising in Astronomy -- K-Subspace Clustering -- Latent Dirichlet Bayesian Co-Clustering -- Variational Graph Embedding for Globally and Locally Consistent Feature Extraction -- Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling -- Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective -- Subspace Regularization: A New Semi-supervised Learning Method -- Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension -- Semi-Supervised Multi-Task Regression -- A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis -- Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns -- Learning the Difference between Partially Observable Dynamical Systems -- Universal Learning over Related Distributions and Adaptive Graph Transduction -- The Feature Importance Ranking Measure -- Demo Papers -- OTTHO: On the Tip of My THOught -- Protecting Sensitive Topics in Text Documents with PROTEXTOR -- Enhanced Web Page Content Visualization with Firefox -- ClusTR: Exploring Multivariate Cluster Correlations and Topic Trends -- Visual OntoBridge: Semi-automatic Semantic Annotation Software -- Semi-automatic Categorization of Videos on VideoLectures.net -- Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype -- Using Temporal Language Models for Document Dating -- Omiotis: A Thesaurus-Based Measure of Text Relatedness -- Found in Translation -- A Community-Based Platform for Machine Learning Experimentation -- TeleComVis: Exploring Temporal Communities in Telecom Networks. |
Record Nr. | UNINA-9910483698703321 |
Berlin ; ; New York, : Springer, c2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|