This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver efficient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions effectively.
The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another significant application is in multi-language Sentiment Analysis, where the model analyzes text in five languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models.
CAML uses CA rules for Unicode character modeling, offering a transparent, interpretable prediction algorithm.
Overall, CAML aims to drive industrial and societal applications of CA, with an emphasis on transparent results and efficient hardware design through CA’s regular, modular, and scalable structure.
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Prof. Dipanwita Roy Chowdhury has received her B.Tech and M.Tech degrees in Computer Science from University of Kolkata and the PhD degree from the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur. She is a Professor in the Department of Computer Science and Engineering, IIT Kharagpur, India. Currently, she is the Head of the Department of Computer Science and Engineering, IIT Kharagpur. Her current research interests are in the field of Cryptography, Error Correcting Code, Cellular Automata, and VLSI Design and Testing. She has guided 15 PhD students and published more than 150 technical papers in International Journals and Conferences. Prof. Roy Chowdhury is the recipient of INSA Young Scientist Award and Associate of Indian Academy of Science. She is a Senior Member of IEEE and the Fellow of Indian National Academy of Engineers (INAE).
Dr. Raju Hazari has graduation (2009) and masters (2013) in Information Technology from Bengal Engineering and Science University, Shibpur, and PhD (2019) in Theoretical Computer Science from Indian Institute of Engineering Science and Technology, Shibpur. He is currently an Assistant Professor in the Department of Computer Science and Engineering at National Institute of Technology, Calicut. His main topics of interest are: Cellular Automata and Machine Learning.
This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver efficient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions effectively.
The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another significant application is in multi-language Sentiment Analysis, where the model analyzes text in five languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models.
CAML uses CA rules for Unicode character modeling, offering a transparent, interpretable prediction algorithm.
Overall, CAML aims to drive industrial and societal applications of CA, with an emphasis on transparent results and efficient hardware design through CA’s regular, modular, and scalable structure.
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Hardcover. Condition: new. Hardcover. This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver ecient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions eectively.The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another signicant application is in multi-language Sentiment Analysis, where the model analyzes text in ve languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models.CAML uses CA rules for Unicode character modeling, oering a transparent, interpretable prediction algorithm.Overall, CAML aims to drive industrial and societal applications of CA, with an emphasis on transparent results and ecient hardware design through CAs regular, modular, and scalable structure. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789819615001
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