{"product_id":"handbook-on-neural-information-processing-9783642366567","title":"Handbook on Neural Information Processing","description":"\u003cp\u003e • Author(s): Monica Bianchini\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: \u003c\/p\u003e\u003cp\u003e Deep architectures \u003c\/p\u003e\u003cp\u003e Recurrent, recursive, and graph neural networks \u003c\/p\u003e\u003cp\u003e Cellular neural networks \u003c\/p\u003e\u003cp\u003e Bayesian networks \u003c\/p\u003e\u003cp\u003e Approximation capabilities of neural networks \u003c\/p\u003e\u003cp\u003e Semi-supervised learning \u003c\/p\u003e\u003cp\u003e Statistical relational learning \u003c\/p\u003e\u003cp\u003e Kernel methods for structured data \u003c\/p\u003e\u003cp\u003e Multiple classifier systems \u003c\/p\u003e\u003cp\u003e Self organisation and modal learning \u003c\/p\u003e\u003cp\u003e Applications to content-based image retrieval, text mining in large document collections, and bioinformatics \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003eThis book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Hardcover","offer_id":45276803825815,"sku":"9783642366567","price":10900.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783642366567.webp?v=1769286692","url":"https:\/\/atlanticbooks.com\/products\/handbook-on-neural-information-processing-9783642366567","provider":"Atlantic Books","version":"1.0","type":"link"}