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Algorithmic learning theory : 17th international conference, ALT 2006, Barcelona, Spain, October 7-10, 2006 : proceedings / / Jose L. Balcazar, Philip M. Long, Frank Stephan, eds
| Algorithmic learning theory : 17th international conference, ALT 2006, Barcelona, Spain, October 7-10, 2006 : proceedings / / Jose L. Balcazar, Philip M. Long, Frank Stephan, eds |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, : Springer, 2006 |
| Descrizione fisica | 1 online resource (XIII, 393 p.) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
BalcazarJose Luis
LongPhilip M StephanFrank (Frank Christian) |
| Collana |
Lecture notes in computer science. Lecture notes in artificial intelligence
LNCS sublibrary. SL 7, Artificial intelligence |
| Soggetto topico |
Computer algorithms
Machine learning |
| ISBN | 3-540-46650-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Editors’ Introduction -- Editors’ Introduction -- Invited Contributions -- Solving Semi-infinite Linear Programs Using Boosting-Like Methods -- e-Science and the Semantic Web: A Symbiotic Relationship -- Spectral Norm in Learning Theory: Some Selected Topics -- Data-Driven Discovery Using Probabilistic Hidden Variable Models -- Reinforcement Learning and Apprenticeship Learning for Robotic Control -- Regular Contributions -- Learning Unions of ?(1)-Dimensional Rectangles -- On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle -- Active Learning in the Non-realizable Case -- How Many Query Superpositions Are Needed to Learn? -- Teaching Memoryless Randomized Learners Without Feedback -- The Complexity of Learning SUBSEQ (A) -- Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data -- Learning and Extending Sublanguages -- Iterative Learning from Positive Data and Negative Counterexamples -- Towards a Better Understanding of Incremental Learning -- On Exact Learning from Random Walk -- Risk-Sensitive Online Learning -- Leading Strategies in Competitive On-Line Prediction -- Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring -- General Discounting Versus Average Reward -- The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection -- Is There an Elegant Universal Theory of Prediction? -- Learning Linearly Separable Languages -- Smooth Boosting Using an Information-Based Criterion -- Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice -- Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence -- Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning -- Unsupervised Slow Subspace-Learning from Stationary Processes -- Learning-Related Complexity of Linear Ranking Functions. |
| Altri titoli varianti | ALT 2006 |
| Record Nr. | UNINA-9910483095403321 |
| Berlin, : Springer, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 3 / / Jose Luis Balcazar ... [et al.] (eds.)
| Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 3 / / Jose Luis Balcazar ... [et al.] (eds.) |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, : Springer, c2010 |
| Descrizione fisica | 1 online resource (XXII, 632 p. 183 illus.) |
| Disciplina | 006.3 |
| Altri autori (Persone) | BalcazarJose Luis |
| Collana | Lecture notes in artificial intelligence |
| Soggetto topico |
Machine learning
Database management |
| ISBN |
1-280-38926-5
9786613567185 3-642-15939-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910484587603321 |
| Berlin, : Springer, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 1 / / Jose Luis Balcazar ... [et al.[ (eds.)
| Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 1 / / Jose Luis Balcazar ... [et al.[ (eds.) |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2010 |
| Descrizione fisica | 1 online resource (XXX, 620 p. 175 illus.) |
| Disciplina | 006.3 |
| Altri autori (Persone) | BalcazarJose Luis |
| Collana | Lecture notes in artificial intelligence |
| Soggetto topico |
Machine learning
Database management |
| ISBN |
1-280-38918-4
9786613567109 3-642-15880-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Talks (Abstracts) -- Mining Billion-Node Graphs: Patterns, Generators and Tools -- Structure Is Informative: On Mining Structured Information Networks -- Intelligent Interaction with the Real World -- Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology -- Hierarchical Learning Machines and Neuroscience of Visual Cortex -- Formal Theory of Fun and Creativity -- Regular Papers -- Porting Decision Tree Algorithms to Multicore Using FastFlow -- On Classifying Drifting Concepts in P2P Networks -- A Unified Approach to Active Dual Supervision for Labeling Features and Examples -- Vector Field Learning via Spectral Filtering -- Weighted Symbols-Based Edit Distance for String-Structured Image Classification -- A Concise Representation of Association Rules Using Minimal Predictive Rules -- Euclidean Distances, Soft and Spectral Clustering on Weighted Graphs -- Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks -- Leveraging Bagging for Evolving Data Streams -- ITCH: Information-Theoretic Cluster Hierarchies -- Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis -- Process Mining Meets Abstract Interpretation -- Smarter Sampling in Model-Based Bayesian Reinforcement Learning -- Predicting Partial Orders: Ranking with Abstention -- Predictive Distribution Matching SVM for Multi-domain Learning -- Kantorovich Distances between Rankings with Applications to Rank Aggregation -- Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition -- Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss -- Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression -- Adaptive Bases for Reinforcement Learning -- Constructing Nonlinear Discriminants from Multiple Data Views -- Learning Algorithms for Link Prediction Based on Chance Constraints -- Sparse Unsupervised Dimensionality Reduction Algorithms -- Asking Generalized Queries to Ambiguous Oracle -- Analysis of Large Multi-modal Social Networks: Patterns and a Generator -- A Cluster-Level Semi-supervision Model for Interactive Clustering -- Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs -- Induction of Concepts in Web Ontologies through Terminological Decision Trees -- Classification with Sums of Separable Functions -- Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information -- Bagging for Biclustering: Application to Microarray Data -- Hub Gene Selection Methods for the Reconstruction of Transcription Networks -- Expectation Propagation for Bayesian Multi-task Feature Selection -- Graphical Multi-way Models -- Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval -- Graph Regularized Transductive Classification on Heterogeneous Information Networks -- Temporal Maximum Margin Markov Network -- Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration. |
| Record Nr. | UNINA-9910483503403321 |
| Berlin ; ; New York, : Springer, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 2 / / Jose Luis Balcazar ... [et al.] (eds.)
| Machine learning and knowledge discovery in databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010 ; proceedings . Part 2 / / Jose Luis Balcazar ... [et al.] (eds.) |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2010 |
| Descrizione fisica | 1 online resource (XXI, 518 p. 145 illus.) |
| Disciplina | 006.3 |
| Altri autori (Persone) | BalcazarJose Luis |
| Collana | Lecture notes in artificial intelligence |
| Soggetto topico |
Machine learning
Database management |
| ISBN |
1-280-38919-2
9786613567116 3-642-15883-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Regular Papers -- Bayesian Knowledge Corroboration with Logical Rules and User Feedback -- Learning an Affine Transformation for Non-linear Dimensionality Reduction -- NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification -- Hidden Conditional Ordinal Random Fields for Sequence Classification -- A Unifying View of Multiple Kernel Learning -- Evolutionary Dynamics of Regret Minimization -- Recognition of Instrument Timbres in Real Polytimbral Audio Recordings -- Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks -- Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction -- Online Knowledge-Based Support Vector Machines -- Learning with Randomized Majority Votes -- Exploration in Relational Worlds -- Efficient Confident Search in Large Review Corpora -- Learning to Tag from Open Vocabulary Labels -- A Robustness Measure of Association Rules -- Automatic Model Adaptation for Complex Structured Domains -- Collective Traffic Forecasting -- On Detecting Clustered Anomalies Using SCiForest -- Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier -- Online Learning in Adversarial Lipschitz Environments -- Summarising Data by Clustering Items -- Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space -- Latent Structure Pattern Mining -- First-Order Bayes-Ball -- Learning from Demonstration Using MDP Induced Metrics -- Demand-Driven Tag Recommendation -- Solving Structured Sparsity Regularization with Proximal Methods -- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models -- Improved MinMax Cut Graph Clustering with Nonnegative Relaxation -- Integrating Constraint Programming and Itemset Mining -- Topic Modeling for Personalized Recommendation of Volatile Items -- Conditional Ranking on Relational Data. |
| Record Nr. | UNINA-9910484301403321 |
| Berlin ; ; New York, : Springer, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||