Advances in Learning Classifier Systems, Pier L. Lanzi; Wolfgang Stolzmann; Stewart W. Wils
Автор: Neamat El Gayar; Josef Kittler; Fabio Roli Название: Multiple Classifier Systems ISBN: 3642121268 ISBN-13(EAN): 9783642121265 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 9th International Workshop on Multiple Classifier Systems, MCS 2010, held in Cairo, Egypt, in April 2010. This book includes contributions that are organized into sessions dealing with classifier combination and classifier selection, diversity, bagging and boosting, and combination of multiple kernels.
Автор: Judy A. Franklin; Tom M. Mitchell; Sebastian Thrun Название: Recent Advances in Robot Learning ISBN: 0792397452 ISBN-13(EAN): 9780792397458 Издательство: Springer Рейтинг: Цена: 23751.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Jeremy Wyatt; John Demiris Название: Advances in Robot Learning ISBN: 3540411623 ISBN-13(EAN): 9783540411628 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Among the topics addressed in these papers are map building for robot navigation, multi-task reinforcement learning, neural network approaches, example- based learning, situated agents, planning maps for mobile robots, path finding, autonomous robots, and biologically inspired approaches.
Автор: Jaume Bacardit; Ester Bernad?-Mansilla; Martin V. Название: Learning Classifier Systems ISBN: 3540881379 ISBN-13(EAN): 9783540881377 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covers post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - hosted by the Genetic and Evolutionary Computation Conference, GECCO. This book features sections on knowledge representation, and analysis of the system.
Автор: Pier Luca Lanzi; Wolfgang Stolzmann; Stewart W. Wi Название: Learning Classifier Systems ISBN: 3540205446 ISBN-13(EAN): 9783540205449 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 5th International Workshop on Learning Classifier Systems, IWLCS 2003, held in Granada, Spain in September 2003 in conjunction with PPSN VII.
Автор: Josef Kittler; Fabio Roli Название: Multiple Classifier Systems ISBN: 3540422846 ISBN-13(EAN): 9783540422846 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining.
Examples of topics which have developed from the advances of ICA, which are covered in the book are:
A unifying probabilistic model for PCA and ICA
Optimization methods for matrix decompositions
Insights into the FastICA algorithm
Unsupervised deep learning
Machine vision and image retrieval
A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning
A diverse set of application fields, ranging from machine vision to science policy data
Contributions from leading researchers in the field
Автор: Sertan Girgin; Manuel Loth; R?mi Munos; Philippe P Название: Recent Advances in Reinforcement Learning ISBN: 3540897216 ISBN-13(EAN): 9783540897217 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the revised and selected papers of the 8th European Workshop on Reinforcement Learning, EWRL 2008, which took place in Villeneuve d`Ascq, France, during June 30 - July 3, 2008.
Название: Recent advances in reinforcement learning ISBN: 0792397053 ISBN-13(EAN): 9780792397052 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addresses research in the Artificial Intelligence and Neural Network communities. This book includes topics such as the theoretical foundations of dynamic programming approaches, the role of prior knowledge, and methods for improving performance of reinforcement-learning techniques.
Автор: Jacek Koronacki; Zbigniew W. Ras; Slawomir T. Wier Название: Advances in Machine Learning II ISBN: 3642051782 ISBN-13(EAN): 9783642051784 Издательство: Springer Рейтинг: Цена: 36197.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: General Issues.- Knowledge-Oriented and Distributed Unsupervised Learning for Concept Elicitation.- Toward Interactive Computations: A Rough-Granular Approach.- Data Privacy: From Technology to Economics.- Adapting to Human Gamers Using Coevolution.- Wisdom of Crowds in the Prisoner's Dilemma Context.- Logical and Relational Learning, and Beyond.- Towards Multistrategic Statistical Relational Learning.- About Knowledge and Inference in Logical and Relational Learning.- Two Examples of Computational Creativity: ILP Multiple Predicate Synthesis and the 'Assets' in Theorem Proving.- Logical Aspects of the Measures of Interestingness of Association Rules.- Text and Web Mining.- Clustering the Web 2.0.- Induction in Multi-Label Text Classification Domains.- Cluster-Lift Method for Mapping Research Activities over a Concept Tree.- On Concise Representations of Frequent Patterns Admitting Negation.- Classification and Beyond.- A System to Detect Inconsistencies between a Domain Expert's Different Perspectives on (Classification) Tasks.- The Dynamics of Multiagent Q-Learning in Commodity Market Resource Allocation.- Simple Algorithms for Frequent Item Set Mining.- Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification.- Machine Learning Methods in Automatic Image Annotation.- Neural Networks and Other Nature Inspired Approaches.- Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework.- Machine Learning in Vector Models of Neural Networks.- Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction.- Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks.- Neural Network and Artificial Immune Systems for Malware and Network Intrusion Detection.- Immunocomputing for Speaker Recognition.
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