- Authors:
- Peiji Liang,
- Si Wu,
- Fanji Gu
This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.
Cited By
- Tan S, Zhao W and Li P (2021). Fast neural ranking on bipartite graph indices, Proceedings of the VLDB Endowment, 15:4, (794-803), Online publication date: 1-Dec-2021.
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- Mitra B (2021). Neural methods for effective, efficient, and exposure-aware information retrieval, ACM SIGIR Forum, 55:1, (1-2), Online publication date: 1-Jun-2021.
- Craswell N, Campos D, Mitra B, Yilmaz E and Billerbeck B ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search Proceedings of the 29th ACM International Conference on Information & Knowledge Management, (2983-2989)
- Dietz L, Mitra B, Pickens J, Anber H, Avula S, Biega A, Boteanu A, Chatterjee S, Dalton J, Dietz L, Dori-Hacohen S, Foley J, Feild H, Gamari B, Jones R, Kanani P, Kashyapi S, Machmouchi W, Mitra B, Mitsui M, Nole S, Passos A, Pickens J, Ramsdell J, Roegiest A, Smith D and Sordoni A (2021). Report on the First HIPstIR Workshop on the Future of Information Retrieval, ACM SIGIR Forum, 53:2, (62-75), Online publication date: 1-Dec-2019.
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- Guo W, Gao H, Shi J and Long B Deep Natural Language Processing for Search Systems Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, (1405-1406)
- CHAIDAROON S, Fang Y, Xie M and Magnani A Neural Compatibility Ranking for Text-based Fashion Matching Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, (1229-1232)
- Rosset C, Mitra B, Xiong C, Craswell N, Song X and Tiwary S An Axiomatic Approach to Regularizing Neural Ranking Models Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, (981-984)
- Markov I and de Rijke M (2019). What Should We Teach in Information Retrieval?, ACM SIGIR Forum, 52:2, (19-39), Online publication date: 17-Jan-2019.
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- Rosset C, Jose D, Ghosh G, Mitra B and Tiwary S Optimizing Query Evaluations Using Reinforcement Learning for Web Search The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, (1193-1196)
- Zamani H, Mitra B, Song X, Craswell N and Tiwary S Neural Ranking Models with Multiple Document Fields Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, (700-708)