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Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNINA-9910484403103321 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNISA-996465748403316 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Learning Theory [[electronic resource] ] : 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / / edited by John Shawe-Taylor, Yoram Singer
| Learning Theory [[electronic resource] ] : 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / / edited by John Shawe-Taylor, Yoram Singer |
| Edizione | [1st ed. 2004.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 |
| Descrizione fisica | 1 online resource (X, 654 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Mathematical logic Algorithms Computers Artificial Intelligence Mathematical Logic and Formal Languages Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
| ISBN | 3-540-27819-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Economics and Game Theory -- Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions -- Graphical Economics -- Deterministic Calibration and Nash Equilibrium -- Reinforcement Learning for Average Reward Zero-Sum Games -- OnLine Learning -- Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability -- Minimizing Regret with Label Efficient Prediction -- Regret Bounds for Hierarchical Classification with Linear-Threshold Functions -- Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary -- Inductive Inference -- Learning Classes of Probabilistic Automata -- On the Learnability of E-pattern Languages over Small Alphabets -- Replacing Limit Learners with Equally Powerful One-Shot Query Learners -- Probabilistic Models -- Concentration Bounds for Unigrams Language Model -- Inferring Mixtures of Markov Chains -- Boolean Function Learning -- PExact = Exact Learning -- Learning a Hidden Graph Using O(log n) Queries Per Edge -- Toward Attribute Efficient Learning of Decision Lists and Parities -- Empirical Processes -- Learning Over Compact Metric Spaces -- A Function Representation for Learning in Banach Spaces -- Local Complexities for Empirical Risk Minimization -- Model Selection by Bootstrap Penalization for Classification -- MDL -- Convergence of Discrete MDL for Sequential Prediction -- On the Convergence of MDL Density Estimation -- Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification -- Generalisation I -- Learning Intersections of Halfspaces with a Margin -- A General Convergence Theorem for the Decomposition Method -- Generalisation II -- Oracle Bounds and Exact Algorithm for Dyadic Classification Trees -- An Improved VC Dimension Bound for Sparse Polynomials -- A New PAC Bound for Intersection-Closed Concept Classes -- Clustering and Distributed Learning -- A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering -- Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers -- Consistency in Models for Communication Constrained Distributed Learning -- On the Convergence of Spectral Clustering on Random Samples: The Normalized Case -- Boosting -- Performance Guarantees for Regularized Maximum Entropy Density Estimation -- Learning Monotonic Linear Functions -- Boosting Based on a Smooth Margin -- Kernels and Probabilities -- Bayesian Networks and Inner Product Spaces -- An Inequality for Nearly Log-Concave Distributions with Applications to Learning -- Bayes and Tukey Meet at the Center Point -- Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results -- Kernels and Kernel Matrices -- A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra -- Statistical Properties of Kernel Principal Component Analysis -- Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA -- Regularization and Semi-supervised Learning on Large Graphs -- Open Problems -- Perceptron-Like Performance for Intersections of Halfspaces -- The Optimal PAC Algorithm -- The Budgeted Multi-armed Bandit Problem. |
| Record Nr. | UNISA-996465807203316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Learning Theory : 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / / edited by John Shawe-Taylor, Yoram Singer
| Learning Theory : 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / / edited by John Shawe-Taylor, Yoram Singer |
| Edizione | [1st ed. 2004.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 |
| Descrizione fisica | 1 online resource (X, 654 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Mathematical logic Algorithms Computers Artificial Intelligence Mathematical Logic and Formal Languages Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
| ISBN | 3-540-27819-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Economics and Game Theory -- Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions -- Graphical Economics -- Deterministic Calibration and Nash Equilibrium -- Reinforcement Learning for Average Reward Zero-Sum Games -- OnLine Learning -- Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability -- Minimizing Regret with Label Efficient Prediction -- Regret Bounds for Hierarchical Classification with Linear-Threshold Functions -- Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary -- Inductive Inference -- Learning Classes of Probabilistic Automata -- On the Learnability of E-pattern Languages over Small Alphabets -- Replacing Limit Learners with Equally Powerful One-Shot Query Learners -- Probabilistic Models -- Concentration Bounds for Unigrams Language Model -- Inferring Mixtures of Markov Chains -- Boolean Function Learning -- PExact = Exact Learning -- Learning a Hidden Graph Using O(log n) Queries Per Edge -- Toward Attribute Efficient Learning of Decision Lists and Parities -- Empirical Processes -- Learning Over Compact Metric Spaces -- A Function Representation for Learning in Banach Spaces -- Local Complexities for Empirical Risk Minimization -- Model Selection by Bootstrap Penalization for Classification -- MDL -- Convergence of Discrete MDL for Sequential Prediction -- On the Convergence of MDL Density Estimation -- Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification -- Generalisation I -- Learning Intersections of Halfspaces with a Margin -- A General Convergence Theorem for the Decomposition Method -- Generalisation II -- Oracle Bounds and Exact Algorithm for Dyadic Classification Trees -- An Improved VC Dimension Bound for Sparse Polynomials -- A New PAC Bound for Intersection-Closed Concept Classes -- Clustering and Distributed Learning -- A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering -- Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers -- Consistency in Models for Communication Constrained Distributed Learning -- On the Convergence of Spectral Clustering on Random Samples: The Normalized Case -- Boosting -- Performance Guarantees for Regularized Maximum Entropy Density Estimation -- Learning Monotonic Linear Functions -- Boosting Based on a Smooth Margin -- Kernels and Probabilities -- Bayesian Networks and Inner Product Spaces -- An Inequality for Nearly Log-Concave Distributions with Applications to Learning -- Bayes and Tukey Meet at the Center Point -- Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results -- Kernels and Kernel Matrices -- A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra -- Statistical Properties of Kernel Principal Component Analysis -- Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA -- Regularization and Semi-supervised Learning on Large Graphs -- Open Problems -- Perceptron-Like Performance for Intersections of Halfspaces -- The Optimal PAC Algorithm -- The Budgeted Multi-armed Bandit Problem. |
| Record Nr. | UNINA-9910767544303321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 | ||
| Materiale a stampa | ||
| 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 / / edited by Wray Buntine, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part II / / edited by Wray Buntine, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 |
| Descrizione fisica | 1 online resource (XXIX, 762 p.) |
| Disciplina | 004.6 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Computer communication systems
Data mining Database management Artificial intelligence Information storage and retrieval Computers Computer Communication Networks Data Mining and Knowledge Discovery Database Management Artificial Intelligence Information Storage and Retrieval Information Systems and Communication Service |
| 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. | UNISA-996465327103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I / / edited by Wray Buntine, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I / / edited by Wray Buntine, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 |
| Descrizione fisica | 1 online resource (XXIX, 756 p.) |
| Disciplina | 006.3/12 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Computer communication systems
Data mining Database management Artificial intelligence Information storage and retrieval Computers Computer Communication Networks Data Mining and Knowledge Discovery Database Management Artificial Intelligence Information Storage and Retrieval Information Systems and Communication Service |
| 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. |
| Record Nr. | UNISA-996465329003316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
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.)
| 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 | ||
| Materiale a stampa | ||
| 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.)
| 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 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Subspace, Latent Structure and Feature Selection [[electronic resource] ] : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / / edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor
| Subspace, Latent Structure and Feature Selection [[electronic resource] ] : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / / edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (X, 209 p.) |
| Disciplina | 003/.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science—Mathematics Mathematical statistics Computer science Artificial intelligence Computer vision Pattern recognition systems Probability and Statistics in Computer Science Theory of Computation Artificial Intelligence Computer Vision Automated Pattern Recognition |
| ISBN | 3-540-34138-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Contributions -- Discrete Component Analysis -- Overview and Recent Advances in Partial Least Squares -- Random Projection, Margins, Kernels, and Feature-Selection -- Some Aspects of Latent Structure Analysis -- Feature Selection for Dimensionality Reduction -- Contributed Papers -- Auxiliary Variational Information Maximization for Dimensionality Reduction -- Constructing Visual Models with a Latent Space Approach -- Is Feature Selection Still Necessary? -- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data -- Incorporating Constraints and Prior Knowledge into Factorization Algorithms – An Application to 3D Recovery -- A Simple Feature Extraction for High Dimensional Image Representations -- Identifying Feature Relevance Using a Random Forest -- Generalization Bounds for Subspace Selection and Hyperbolic PCA -- Less Biased Measurement of Feature Selection Benefits. |
| Record Nr. | UNISA-996465879603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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