2008, ISBN: 9783540879862
This volume contains papers presented at the 19th International Conference on Algorithmic Learning Theory (ALT 2008), which was held in Budapest, Hungary during October 13–16, 2008. The c… Mehr…
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Algorithmic Learning Theory: 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) - Taschenbuch
2008, ISBN: 9783540879862
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Algorithmic Learning Theory: 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings (Lecture Notes in Computer Science, 5254) - Taschenbuch
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2008, ISBN: 9783540879862
This volume contains papers presented at the 19th International Conference on Algorithmic Learning Theory (ALT 2008), which was held in Budapest, Hungary during October 13–16, 2008. The c… Mehr…
Freund, Yoav Gyoerfi, László Turán, Gyoergy Zeugmann, Thomas:
Algorithmic Learning Theory - Taschenbuch2008, ISBN: 9783540879862
[ED: Kartoniert / Broschiert], [PU: Springer Berlin Heidelberg], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This volume contains pape… Mehr…
Algorithmic Learning Theory: 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) - Taschenbuch
2008
ISBN: 9783540879862
Springer, 2008-11-17. Paperback. Very Good. Ex-library paperback in very nice condition with the usual markings and attachments., Springer, 2008-11-17, 3
Algorithmic Learning Theory: 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings (Lecture Notes in Computer Science, 5254) - Taschenbuch
2008, ISBN: 9783540879862
Springer. Paperback. GOOD. Spine creases, wear to binding and pages from reading. May contain limited notes, underlining or highlighting that does affect the text. Possible ex library c… Mehr…
2008, ISBN: 9783540879862
*Algorithmic Learning Theory* - 19th International Conference ALT 2008 Budapest Hungary October 13-16 2008 Proceedings. Auflage 2008 / Taschenbuch für 53.49 € / Aus dem Bereich: Bücher, R… Mehr…
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Detailangaben zum Buch - Algorithmic Learning Theory
EAN (ISBN-13): 9783540879862
ISBN (ISBN-10): 3540879862
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2008
Herausgeber: Springer Berlin Heidelberg
467 Seiten
Gewicht: 0,724 kg
Sprache: eng/Englisch
Buch in der Datenbank seit 2008-11-29T18:03:07+01:00 (Berlin)
Detailseite zuletzt geändert am 2024-01-29T10:25:34+01:00 (Berlin)
ISBN/EAN: 9783540879862
ISBN - alternative Schreibweisen:
3-540-87986-2, 978-3-540-87986-2
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: laszlo, thomas freund, györgy, turan, tura, yoav, lászló, budapest
Titel des Buches: proceedings international conference, alt, algorithmic learning theory, international conference computer science, october, bildfolien learning, greetings from old budapest, hungary, freund, lecture notes artificial intelligence
Daten vom Verlag:
Autor/in: Yoav Freund; László Györfi; György Turán; Thomas Zeugmann
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Algorithmic Learning Theory - 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings
Verlag: Springer; Springer Berlin
467 Seiten
Erscheinungsjahr: 2008-09-29
Berlin; Heidelberg; DE
Sprache: Englisch
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
XIII, 467 p.
BC; Hardcover, Softcover / Informatik, EDV/Informatik; Data Mining; Verstehen; Informatik; Clustering; comlexity; concept spaces; half-space learning; language learning; learning; machine learning; markov process; neural representation; visual datamining; visualization; Data Mining and Knowledge Discovery; Artificial Intelligence; Natural Language Processing (NLP); Digital Humanities; Wissensbasierte Systeme, Expertensysteme; Künstliche Intelligenz; Natürliche Sprachen und maschinelle Übersetzung; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Computer-Anwendungen in Kunst und Geisteswissenschaften; EA
Invited Papers.- On Iterative Algorithms with an Information Geometry Background.- Visual Analytics: Combining Automated Discovery with Interactive Visualizations.- Some Mathematics behind Graph Property Testing.- Finding Total and Partial Orders from Data for Seriation.- Computational Models of Neural Representations in the Human Brain.- Regular Contributions.- Generalization Bounds for Some Ordinal Regression Algorithms.- Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm.- Sample Selection Bias Correction Theory.- Exploiting Cluster-Structure to Predict the Labeling of a Graph.- A Uniform Lower Error Bound for Half-Space Learning.- Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces.- Learning and Generalization with the Information Bottleneck.- Growth Optimal Investment with Transaction Costs.- Online Regret Bounds for Markov Decision Processes with Deterministic Transitions.- On-Line Probability, Complexity and Randomness.- Prequential Randomness.- Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor.- Nonparametric Independence Tests: Space Partitioning and Kernel Approaches.- Supermartingales in Prediction with Expert Advice.- Aggregating Algorithm for a Space of Analytic Functions.- Smooth Boosting for Margin-Based Ranking.- Learning with Continuous Experts Using Drifting Games.- Entropy Regularized LPBoost.- Optimally Learning Social Networks with Activations and Suppressions.- Active Learning in Multi-armed Bandits.- Query Learning and Certificates in Lattices.- Clustering with Interactive Feedback.- Active Learning of Group-Structured Environments.- Finding the Rare Cube.- Iterative Learning of Simple External Contextual Languages.- Topological Properties of Concept Spaces.- Dynamically Delayed Postdictive Completeness and Consistency in Learning.- Dynamic Modeling in Inductive Inference.- Optimal Language Learning.- Numberings Optimal for Learning.- Learning with Temporary Memory.- Erratum: Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors.Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
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