Inductive Logic Programming [[electronic resource] ] : 11th International Conference, ILP 2001, Strasbourg, France, September 9-11, 2001. Proceedings / / edited by Celine Rouveirol, Michele Sebag |
Edizione | [1st ed. 2001.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
Descrizione fisica | 1 online resource (IX, 259 p.) |
Disciplina | 005.1/15 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Architecture, Computer
Software engineering Artificial intelligence Computer programming Mathematical logic Algorithms Computer System Implementation Software Engineering/Programming and Operating Systems Artificial Intelligence Programming Techniques Mathematical Logic and Formal Languages Algorithm Analysis and Problem Complexity |
ISBN | 3-540-44797-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Refinement Operator for Theories -- Learning Logic Programs with Neural Networks -- A Genetic Algorithm for Propositionalization -- Classifying Uncovered Examples by Rule Stretching -- Relational Learning Using Constrained Confidence-Rated Boosting -- Induction, Abduction, and Consequence-Finding -- From Shell Logs to Shell Scripts -- An Automated ILP Server in the Field of Bioinformatics -- Adaptive Bayesian Logic Programs -- Towards Combining Inductive Logic Programming with Bayesian Networks -- Demand-Driven Construction of Structural Features in ILP -- Transformation-Based Learning Using Multirelational Aggregation -- Discovering Associations between Spatial Objects: An ILP Application -- ?-Subsumption in a Constraint Satisfaction Perspective -- Learning to Parse from a Treebank: Combining TBL and ILP -- Induction of Stable Models -- Application of Pruning Techniques for Propositional Learning to Progol -- Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition -- Efficient Cross-Validation in ILP -- Modelling Semi-structured Documents with Hedges for Deduction and Induction -- Learning Functions from Imperfect Positive Data. |
Record Nr. | UNISA-996465810803316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Inductive Logic Programming : 11th International Conference, ILP 2001, Strasbourg, France, September 9-11, 2001. Proceedings / / edited by Celine Rouveirol, Michele Sebag |
Edizione | [1st ed. 2001.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
Descrizione fisica | 1 online resource (IX, 259 p.) |
Disciplina | 005.1/15 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Architecture, Computer
Software engineering Artificial intelligence Computer programming Mathematical logic Algorithms Computer System Implementation Software Engineering/Programming and Operating Systems Artificial Intelligence Programming Techniques Mathematical Logic and Formal Languages Algorithm Analysis and Problem Complexity |
ISBN | 3-540-44797-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Refinement Operator for Theories -- Learning Logic Programs with Neural Networks -- A Genetic Algorithm for Propositionalization -- Classifying Uncovered Examples by Rule Stretching -- Relational Learning Using Constrained Confidence-Rated Boosting -- Induction, Abduction, and Consequence-Finding -- From Shell Logs to Shell Scripts -- An Automated ILP Server in the Field of Bioinformatics -- Adaptive Bayesian Logic Programs -- Towards Combining Inductive Logic Programming with Bayesian Networks -- Demand-Driven Construction of Structural Features in ILP -- Transformation-Based Learning Using Multirelational Aggregation -- Discovering Associations between Spatial Objects: An ILP Application -- ?-Subsumption in a Constraint Satisfaction Perspective -- Learning to Parse from a Treebank: Combining TBL and ILP -- Induction of Stable Models -- Application of Pruning Techniques for Propositional Learning to Progol -- Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition -- Efficient Cross-Validation in ILP -- Modelling Semi-structured Documents with Hedges for Deduction and Induction -- Learning Functions from Imperfect Positive Data. |
Record Nr. | UNINA-9910143626803321 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Machine Learning: ECML-98 [[electronic resource] ] : 10th European Conference on Machine Learning, Chemnitz, Germany, April 21-23, 1998, Proceedings / / edited by Claire Nedellec, Celine Rouveirol |
Edizione | [1st ed. 1998.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1998 |
Descrizione fisica | 1 online resource (XIV, 426 p.) |
Disciplina | 006.3/1 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Artificial intelligence
Algorithms Artificial Intelligence Algorithm Analysis and Problem Complexity |
ISBN | 3-540-69781-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Learning in agent-oriented worlds -- Naive (Bayes) at forty: The independence assumption in information retrieval -- Learning verbal transitivity using loglinear models -- Part-of-speech tagging using decision trees -- Inference of finite automata: Reducing the search space with an ordering of pairs of states -- Automatic acquisition of lexical knowledge from sparse and noisy data -- A normalization method for contextual data: Experience from a large-scale application -- Learning to classify x-ray images using relational learning -- ILP experiments in detecting traffic problems -- Simulating children learning and explaining elementary heat transfer phenomena: A multistrategy system at work -- Bayes optimal instance-based learning -- Bayesian and information-theoretic priors for Bayesian network parameters -- Feature subset selection in text-learning -- A monotonic measure for optimal feature selection -- Inducing models of human control skills -- God doesn't always shave with Occam's razor — Learning when and how to prune -- Error estimators for pruning regression trees -- Pruning decision trees with misclassification costs -- Text categorization with Support Vector Machines: Learning with many relevant features -- A short note about the application of polynomial kernels with fractional degree in Support Vector Learning -- Classification learning using all rules -- Improved pairwise coupling classification with correcting classifiers -- Experiments on solving multiclass learning problems by n 2-classifier -- Combining classifiers by constructive induction -- Boosting trees for cost-sensitive classifications -- Naive bayesian classifier committees -- Batch classifications with discrete finite mixtures -- Induction of recursive program schemes -- Predicate invention and learning from positive examples only -- An inductive logic programming framework to learn a concept from ambiguous examples -- First-order learning for Web mining -- Explanation-based generalization in game playing: Quantitative results -- Scope classification: An instance-based learning algorithm with a rule-based characterisation -- Error-correcting output codes for local learners -- Recursive lazy learning for modeling and control -- Using lattice-based framework as a tool for feature extraction -- Determining property relevance in concept formation by computing correlation between properties -- A buffering strategy to avoid ordering effects in clustering -- Coevolutionary, distributed search for inducing concept descriptions -- Continuous mimetic evolution -- A host-parasite genetic algorithm for asymmetric tasks -- Speeding up Q(?)-learning -- Q-learning and redundancy reduction in classifier systems with internal state -- Composing functions to speed up reinforcement learning in a changing world -- Theoretical results on reinforcement learning with temporally abstract options -- A general convergence method for Reinforcement Learning in the continuous case -- Interpretable neural networks with BP-SOM -- Convergence rate of minimization learning for neural networks. |
Record Nr. | UNINA-9910144913103321 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1998 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Machine Learning: ECML-98 [[electronic resource] ] : 10th European Conference on Machine Learning, Chemnitz, Germany, April 21-23, 1998, Proceedings / / edited by Claire Nedellec, Celine Rouveirol |
Edizione | [1st ed. 1998.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1998 |
Descrizione fisica | 1 online resource (XIV, 426 p.) |
Disciplina | 006.3/1 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Artificial intelligence
Algorithms Artificial Intelligence Algorithm Analysis and Problem Complexity |
ISBN | 3-540-69781-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Learning in agent-oriented worlds -- Naive (Bayes) at forty: The independence assumption in information retrieval -- Learning verbal transitivity using loglinear models -- Part-of-speech tagging using decision trees -- Inference of finite automata: Reducing the search space with an ordering of pairs of states -- Automatic acquisition of lexical knowledge from sparse and noisy data -- A normalization method for contextual data: Experience from a large-scale application -- Learning to classify x-ray images using relational learning -- ILP experiments in detecting traffic problems -- Simulating children learning and explaining elementary heat transfer phenomena: A multistrategy system at work -- Bayes optimal instance-based learning -- Bayesian and information-theoretic priors for Bayesian network parameters -- Feature subset selection in text-learning -- A monotonic measure for optimal feature selection -- Inducing models of human control skills -- God doesn't always shave with Occam's razor — Learning when and how to prune -- Error estimators for pruning regression trees -- Pruning decision trees with misclassification costs -- Text categorization with Support Vector Machines: Learning with many relevant features -- A short note about the application of polynomial kernels with fractional degree in Support Vector Learning -- Classification learning using all rules -- Improved pairwise coupling classification with correcting classifiers -- Experiments on solving multiclass learning problems by n 2-classifier -- Combining classifiers by constructive induction -- Boosting trees for cost-sensitive classifications -- Naive bayesian classifier committees -- Batch classifications with discrete finite mixtures -- Induction of recursive program schemes -- Predicate invention and learning from positive examples only -- An inductive logic programming framework to learn a concept from ambiguous examples -- First-order learning for Web mining -- Explanation-based generalization in game playing: Quantitative results -- Scope classification: An instance-based learning algorithm with a rule-based characterisation -- Error-correcting output codes for local learners -- Recursive lazy learning for modeling and control -- Using lattice-based framework as a tool for feature extraction -- Determining property relevance in concept formation by computing correlation between properties -- A buffering strategy to avoid ordering effects in clustering -- Coevolutionary, distributed search for inducing concept descriptions -- Continuous mimetic evolution -- A host-parasite genetic algorithm for asymmetric tasks -- Speeding up Q(?)-learning -- Q-learning and redundancy reduction in classifier systems with internal state -- Composing functions to speed up reinforcement learning in a changing world -- Theoretical results on reinforcement learning with temporally abstract options -- A general convergence method for Reinforcement Learning in the continuous case -- Interpretable neural networks with BP-SOM -- Convergence rate of minimization learning for neural networks. |
Record Nr. | UNISA-996466084803316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1998 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|