"Computational Trust Models and Machine Learning"

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Book	Author(s)	Year	Publisher
Computational Trust Models and Machine Learning	Xin Liu; Anwitaman Datta; Ee-Peng Lim	2014	Routledge
Data-Driven Computational Neuroscience: Machine Learning and Statistical Models	Concha Bielza; Pedro Larrañaga	2020-11	Cambridge University Press
Computational Models of Learning	Leonard Bolc	1987	Springer Berlin Heidelberg
Computational models of learning /	Bolc, Leonard,; Bradshaw, G. L.	1987.	Springer-Verlag,
The computational complexity of machine learning	Michael J. Kearns	1990	MIT Press
Computational Intelligence for Machine Learning and Healthcare Informatics	Rajshree Srivastava; Pradeep Kumar Mallick; Siddharth Swarup Rautaray; Manjusha Pandey	2020	De Gruyter
Practical MLOps: Operationalizing Machine Learning Models	Noah Gift, Alfredo Deza	2021	O'Reilly Media
Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient	Tanay Agrawal	1st ed.	Apress
Computational Learning Theory and Natural Learning Systems: Selecting Good Models	Thomas Petsche; Stephen José Hanson; Jude Shavlik	1995	MIT Press,
Graphical Models for Machine Learning and Digital Communication	Brendan J. Frey	1998	MIT Press
Graphical Models for Machine Learning and Digital Communication	Brendan J. Frey	1998	MIT Press,
Machine Learning in Cyber Trust: Security, Privacy, and Reliability	Jeffrey J. P. Tsai; Philip S. Yu	2009	Springer US
Computational and Machine Learning Tools for Archaeological Site Modeling	Maria Elena Castiello	1st ed. 2022	Springer International Publishing
Learn PySpark: Build Python-based Machine Learning and Deep Learning Models	Pramod Singh	1st ed.	Apress
Hardware-Aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases	Laura Isabel Galindez Olascoaga; Wannes Meert; Marian Verhelst	1st ed. 2021	Springer International Publishing
Ambiguity resolution in language learning: computational and cognitive models /	Schütze, Hinrich.	[1997], ©1997.	CSLI Publications,
MACHINE LEARNING WITH PYTORCH AND SCIKIT-LEARN: develop machine learning and deep learning. . . models with scikit-learn and pytorch.	SEBASTIAN LIU YUXI (HAYDEN) MIRJALILI VAHID RASCHKA	2022	PACKT PUBLISHING LIMITED
Machine Learning and Optimization Models for Optimization in Cloud	Punit Gupta; Mayank Kumar Goyal; Sudeshna Chakraborty; Ahmed A Elngar	2022	Routledge
Computational Models of Learning in Simple Neural Systems	Robert D. Hawkins; Gordon H. Bower	1989	Academic Press
Optimization and Machine Learning - Optimizationfor Machine Learning and Machine Learning for Optimization	Rachid Chelouah; Patrick Siarry	2022	John Wiley & Sons
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Showing 1 to 20 of 100 entries

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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Computational Trust Models	Xin Liu; Anwitaman Datta; Karl Aberer	Encyclopedia of Social Network Analysis and Mining	Reda Alhajj; Jon Rokne	2014	Springer New York
Computational Trust Models	Xin Liu; Anwitaman Datta; Karl Aberer	Encyclopedia of Social Network Analysis and Mining	Reda Alhajj; Jon Rokne	2nd ed. 2018	Springer New York
Computational Trust Models	Xin Liu; Anwitaman Datta; Karl Aberer	Encyclopedia of Social Network Analysis and Mining	Reda Alhajj; Jon Rokne	0th ed. 2020	Springer New York
Computational learning (machine learning)		Biosignal Processing and Classification Using Computational Learning and Intelligence	Alejandro Torres-García; Carlos Reyes Garcia; Luis Villasenor-Pineda and Omar Mendoza-Montoya	2022	Academic Press
Machine Learning Models		Internet of Energy for Smart Cities: Machine Learning Models and Techniques	Anish Jindal; Neeraj Kumar; Gagangeet Singh Aujla	2021	Routledge
Machine learning models		Machine Learning Theory to Applications: Theory to Applications	Seyedeh Leili Mirtaheri, Reza Shahbazian	2022	CRC Press
Machine learning models		IoT and Edge Computing for Architects: Implementing edge and IoT systems from sensors to clouds with communication systems, analytics, and security, 2nd Edition	Perry Lea	2020	Packt Publishing
Machine Learning Models	Guanghui Lan	First-order and Stochastic Optimization Methods for Machine Learning	Guanghui Lan	1st ed. 2020	Springer International Publishing
Machine Learning Models	Jacques Savoy	Machine Learning Methods for Stylometry: Authorship Attribution and Author Profiling	Jacques Savoy	1st ed. 2020	Springer International Publishing
Trinity: Trust, Resilience and Interpretability of Machine Learning Models		Game Theory and Machine Learning for Cyber Security	Charles A. Kamhoua; Christopher D. Kiekintveld; Fei Fang; Quanyan Zhu	2021	Wiley-IEEE Press
Structure-Based Machine Learning Models for Computational Mutagenesis	Majid Masso; Iosif I. Vaisman	Introduction to Protein Structure Prediction: Methods and Algorithms	Huzefa Rangwala	2010	John Wiley & Sons
Computational Models of Learning		Encyclopedia of the Sciences of Learning	Norbert M. Seel	2012	Springer US
4: Computational Intelligence and Machine Learning		Algorithms Are Not Enough: Creating General Artificial Intelligence	Herbert L. Roitblat	2020	MIT Press,
4 Computational Intelligence and Machine Learning		Algorithms Are Not Enough: Creating General Artificial Intelligence	Herbert L. Roitblat	2020	MIT Press
Machine Learning in Computational Biology	Cornelia Caragea; Vasant Honavar	Encyclopedia of Database Systems	Ling Liu; M. Tamer Özsu	2009	Springer US
Machine Learning in Computational Biology	Cornelia Caragea; Vasant Honavar	Encyclopedia of Database Systems	Ling Liu; M. Tamer Özsu	2nd ed. 2018	Springer New York
Machine Learning in Computational Biology	Cornelia Caragea; Vasant Honavar	Encyclopedia of Database Systems	Ling Liu; M. Tamer Özsu	0th ed. 2020	Springer New York
1211 Machine Learning and Models		Information Security Management	Michael Workman	2021	Jones & Bartlett Learning
Statistical and Machine Learning Models		The Statistics and Calculus with Python Workshop: A comprehensive introduction to mathematics in Python for artificial intelligence applications	Peter Farrell, Alvaro Fuentes, Ajinkya Sudhir Kolhe, Quan Nguyen, Alexander Joseph Sarver, Marios Tsatsos	2020	Packt Publishing
Learning Topology: Bridging Computational Topology and Machine Learning	Davide Moroni; Maria Antonietta Pascali	Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part V	Alberto Del Bimbo; Rita Cucchiara; Stan Sclaroff; Giovanni Maria Farinella; Tao Mei; Marco Bertini; Hugo Jair Escalante; Roberto Vezzani	1st ed. 2021	Springer International Publishing
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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