Meta-Learning in Computational Intelligence.pdf

Meta-Learning in Computational Intelligence

Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open.
Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which  these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process.
This is where algorithms that learn how to learnl come to rescue.
Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn.
This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.

23 Aug 2019 ... Some schools of thought within the artificial intelligence(AI) community subscribe to the thesis that meta-learning is one of the stepping stones ... 16 Oct 2019 ... Meta-Learning is the most promising paradigm to advance the state-of-the-art of Deep Learning and Artificial Intelligence. OpenAI set the AI ...

3642268587 ISBN
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Meta-Learning in Computational Intelligence.pdf


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Meta-Learning in Computational Intelligence (Studies in Computational Intelligence, Band 358) | Norbert Jankowski, Wlodzislaw Duch, Krzysztof Grąbczewski | ISBN: 9783642268588 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

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Meta-learning in computational intelligence. N Jankowski, W Duch, ... Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 6 pp., 2005. 40, 2005.

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One of the major challenges in many domains of Computational Intelligence,. Machine Learning, Data Analysis and other fields is to investigate the capabili-.

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24.11.2018 · Introduction to the special issue on meta-learning. Machine learning, 54(3):187–193, 2004. [16] Jankowski, Norbert, Duch, Włodzisław, and Grabczewski, Krzysztof. Meta-learning in computational intelligence, volume 358. Springer Science & Business Media, 2011. [17] N. E. Cotter and P. R. Conwell. Fixed-weight networks can learn. In Meta-learning with memory-augmented neural …