Algorithmic Learning for Knowledge-Based Systems [[electronic resource] ] : GOSLER Final Report / / edited by Klaus P. Jantke, Steffen Lange |
Edizione | [1st ed. 1995.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1995 |
Descrizione fisica | 1 online resource (X, 522 p.) |
Disciplina | 006.3/3 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Computers
Artificial intelligence Mathematical logic Theory of Computation Artificial Intelligence Mathematical Logic and Formal Languages |
ISBN | 3-540-44737-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Learning and consistency -- Error detecting in inductive inference -- Learning from good examples -- Towards reduction arguments for FINite learning -- Not-so-nearly-minimal-size program inference (preliminary report) -- Optimization problem in inductive inference -- On identification by teams and probabilistic machines -- Topological considerations in composing teams of learning machines -- Probabilistic versus deterministic memory limited learning -- Classification using information -- Classifying recursive predicates and languages -- A guided tour across the boundaries of learning recursive languages -- Pattern inference -- Inductive learning of recurrence-term languages from positive data -- Learning formal languages based on control sets -- Learning in case-based classification algorithms -- Optimal strategies — Learning from examples — Boolean equations -- Feature construction during tree learning -- On lower bounds for the depth of threshold circuits with weights from {?1,0,+1} -- Structuring neural networks and PAC-Learning -- Inductive synthesis of rewrite programs -- TLPS — A term rewriting laboratory (not only) for experiments in automatic program synthesis -- GoslerP — A logic programming tool for inductive inference. |
Record Nr. | UNISA-996466130703316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1995 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Discovery Science [[electronic resource] ] : 5th International Conference, DS 2002, Lubeck, Germany, November 24-26, 2002, Proceedings / / edited by Steffen Lange, Ken Satoh, Carl H. Smith |
Edizione | [1st ed. 2002.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
Descrizione fisica | 1 online resource (XIV, 470 p.) |
Disciplina | 501 |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Database management
Philosophy and science Computer science Information storage and retrieval Artificial intelligence Information technology Business—Data processing Database Management Philosophy of Science Computer Science, general Information Storage and Retrieval Artificial Intelligence IT in Business |
ISBN | 3-540-36182-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Invited Talks -- Mathematics Based on Learning -- Data Mining with Graphical Models -- On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum -- In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project -- Learning Structure from Sequences, with Applications in a Digital Library -- Regular Papers -- Discovering Frequent Structured Patterns from String Databases: An Application to Biological Sequences -- Discovery in Hydrating Plaster Using Machine Learning Methods -- Revising Qualitative Models of Gene Regulation -- SEuS: Structure Extraction Using Summaries -- Discovering Best Variable-Length-Don’t-Care Patterns -- A Study on the Effiect of Class Distribution Using Cost-Sensitive Learning -- Model Complexity and Algorithm Selection in Classification -- Experiments with Projection Learning -- Improved Dataset Characterisation for Meta-learning -- Racing Committees for Large Datasets -- From Ensemble Methods to Comprehensible Models -- Learning the Causal Structure of Overlapping Variable Sets -- Extraction of Logical Rules from Data by Means of Piecewise-Linear Neural Networks -- Structuring Neural Networks through Bidirectional Clustering of Weights -- Toward Drawing an Atlas of Hypothesis Classes: Approximating a Hypothesis via Another Hypothesis Model -- Datascape Survey Using the Cascade Model -- Learning Hierarchical Skills from Observation -- Poster Papers -- Image Analysis for Detecting Faulty Spots from Microarray Images -- Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data Using Differential Equations -- DNA-Tract Curvature Profile Reconstruction: A Fragment Flipping Algorithm -- Evolution Map: Modeling State Transition of Typhoon Image Sequences by Spatio-Temporal Clustering -- Structure-Sweetness Relationships of Aspartame Derivatives by GUHA -- A Hybrid Approach for Chinese Named Entity Recognition -- Extraction of Word Senses from Human Factors in Knowledge Discovery -- Event Pattern Discovery from the Stock Market Bulletin -- Email Categorization Using Fast Machine Learning Algorithms -- Discovery of Maximal Analogies between Stories -- Automatic Wrapper Generation for Multilingual Web Resources -- Combining Multiple K-Nearest Neighbor Classifiers for Text Classification by Reducts -- ARISTA Causal Knowledge Discovery from Texts -- Knowledge Discovery as Applied to Music: Will Music Web Retrieval Revolutionize Musicology? -- Process Mining: Discovering Direct Successors in Process Logs -- The Emergence of Artificial Creole by the EM Algorithm -- Generalized Musical Pattern Discovery by Analogy from Local Viewpoints -- Using Genetic Algorithms-Based Approach for Better Decision Trees: A Computational Study -- Handling Feature Ambiguity in Knowledge Discovery from Time Series -- A Compositional Framework for Mining Longest Ranges -- Post-processing Operators for Browsing Large Sets of Association Rules -- Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction -- Feature Selection for Propositionalization -- Subspace Clustering Based on Compressibility -- The Extra-Theoretical Dimension of Discovery Extracting Knowledge by Abduction -- Discovery Process on the WWW: Analysis Based on a Theory of Scientific Discovery -- Invention vs. Discovery A Critical Discussion. |
Record Nr. | UNISA-996466195103316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Discovery Science : 5th International Conference, DS 2002, Lubeck, Germany, November 24-26, 2002, Proceedings / / edited by Steffen Lange, Ken Satoh, Carl H. Smith |
Edizione | [1st ed. 2002.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
Descrizione fisica | 1 online resource (XIV, 470 p.) |
Disciplina | 501 |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Database management
Philosophy and science Computer science Information storage and retrieval Artificial intelligence Information technology Business—Data processing Database Management Philosophy of Science Computer Science, general Information Storage and Retrieval Artificial Intelligence IT in Business |
ISBN | 3-540-36182-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Invited Talks -- Mathematics Based on Learning -- Data Mining with Graphical Models -- On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum -- In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project -- Learning Structure from Sequences, with Applications in a Digital Library -- Regular Papers -- Discovering Frequent Structured Patterns from String Databases: An Application to Biological Sequences -- Discovery in Hydrating Plaster Using Machine Learning Methods -- Revising Qualitative Models of Gene Regulation -- SEuS: Structure Extraction Using Summaries -- Discovering Best Variable-Length-Don’t-Care Patterns -- A Study on the Effiect of Class Distribution Using Cost-Sensitive Learning -- Model Complexity and Algorithm Selection in Classification -- Experiments with Projection Learning -- Improved Dataset Characterisation for Meta-learning -- Racing Committees for Large Datasets -- From Ensemble Methods to Comprehensible Models -- Learning the Causal Structure of Overlapping Variable Sets -- Extraction of Logical Rules from Data by Means of Piecewise-Linear Neural Networks -- Structuring Neural Networks through Bidirectional Clustering of Weights -- Toward Drawing an Atlas of Hypothesis Classes: Approximating a Hypothesis via Another Hypothesis Model -- Datascape Survey Using the Cascade Model -- Learning Hierarchical Skills from Observation -- Poster Papers -- Image Analysis for Detecting Faulty Spots from Microarray Images -- Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data Using Differential Equations -- DNA-Tract Curvature Profile Reconstruction: A Fragment Flipping Algorithm -- Evolution Map: Modeling State Transition of Typhoon Image Sequences by Spatio-Temporal Clustering -- Structure-Sweetness Relationships of Aspartame Derivatives by GUHA -- A Hybrid Approach for Chinese Named Entity Recognition -- Extraction of Word Senses from Human Factors in Knowledge Discovery -- Event Pattern Discovery from the Stock Market Bulletin -- Email Categorization Using Fast Machine Learning Algorithms -- Discovery of Maximal Analogies between Stories -- Automatic Wrapper Generation for Multilingual Web Resources -- Combining Multiple K-Nearest Neighbor Classifiers for Text Classification by Reducts -- ARISTA Causal Knowledge Discovery from Texts -- Knowledge Discovery as Applied to Music: Will Music Web Retrieval Revolutionize Musicology? -- Process Mining: Discovering Direct Successors in Process Logs -- The Emergence of Artificial Creole by the EM Algorithm -- Generalized Musical Pattern Discovery by Analogy from Local Viewpoints -- Using Genetic Algorithms-Based Approach for Better Decision Trees: A Computational Study -- Handling Feature Ambiguity in Knowledge Discovery from Time Series -- A Compositional Framework for Mining Longest Ranges -- Post-processing Operators for Browsing Large Sets of Association Rules -- Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction -- Feature Selection for Propositionalization -- Subspace Clustering Based on Compressibility -- The Extra-Theoretical Dimension of Discovery Extracting Knowledge by Abduction -- Discovery Process on the WWW: Analysis Based on a Theory of Scientific Discovery -- Invention vs. Discovery A Critical Discussion. |
Record Nr. | UNINA-9910208852403321 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 | ||
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Lo trovi qui: Univ. Federico II | ||
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