This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:
- Deep architectures
- Recurrent, recursive, and graph neural networks
- Cellular neural networks
- Bayesian networks
- Approximation capabilities of neural networks
- Semi-supervised learning
- Statistical relational learning
- Kernel methods for structured data
- Multiple classifier systems
- Self organisation and modal learning
- Applications to content-based image retrieval, text mining in large document collections, and bioinformatics
This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.
€149.79
表中的内容
Neural Network Architectures.- Learning paradigms.-
Reasoning and applications.- conclusions.
Reasoning and applications.- conclusions.
Reasoning and applications.- conclusions.
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语言 英语 ● 格式 PDF ● 网页 538 ● ISBN 9783642366574 ● 文件大小 11.7 MB ● 编辑 Monica Bianchini & Marco Maggini ● 出版者 Springer Berlin ● 市 Heidelberg ● 国家 DE ● 发布时间 2013 ● 下载 24 个月 ● 货币 EUR ● ID 2685044 ● 复制保护 社会DRM
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