Bayesian Methods for Interaction and Design
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Product details:
- Publisher Cambridge University Press
- Date of Publication 25 August 2022
- ISBN 9781108834995
- Binding Hardback
- No. of pages400 pages
- Size 235x157x26 mm
- Weight 670 g
- Language English 432
Categories
Short description:
Introduces Bayesian methods and their implementation in application ranging from pointing-based interfaces to modelling cognitive processes.
MoreLong description:
Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesian optimisation; and Bayesian approaches to modelling the cognitive processes of users.
'More than half a century since network flow theory was introduced by the 1962 book of L.R. Ford and D.R. Fulkerson, the area is still active and attractive. This book, based on course materials taught at Stanford and Cornell Universities, offers a concise and succinct description of most of the important topics, as well as covering recent developments. Its use in graduate courses related to algorithms and optimization is highly recommended.' Toshihide Ibaraki, Kyoto College of Graduate Studies for Informatics
Table of Contents:
Preface Nikola Banovic, Per Ola Kristensson, Antti Oulasvirta and John H. Williamson; Part I. Introduction to Bayesian Methods: 1. An introduction to Bayesian methods for interaction design John H. Williamson; 2. Bayesian statistics Alan Dix; Part II. Probabilistic Interfaces and Inference of Intent: 3. Bayesian information gain to design interaction Wanyu Liu, Olivier Rioul and Michel Beaudouin-Lafon; 4. Bayesian command selection Suwen Zhu, Xiangmin Fan, Feng Tian and Xiaojun Bi; 5. Probabilistic UI representation and reasoning in touch interfaces Daniel Buschek; 6. Statistical keyboard decoding Dylan Gaines, John Dudley, Per Ola Kristensson and Keith Vertanen; 7. Human-Computer interaction design and inverse problems Roderick Murray-Smith, John H. Williamson and Francesco Tonolini; Part III. Bayesian Optimisation in Interaction Design: 8. Preferential Bayesian optimisation for visual design Yuki Koyama, Toby Chong and Takeo Igarashi; 9. Bayesian optimisation of interface features John Dudley and Per Ola Kristensson; Part IV. Bayesian Cognitive Modelling: 10. Cue integration in input performance Byungjoo Lee; 11. Bayesian parameter inference for cognitive simulators Jussi P.P. Jokinen, Ulpu Remes, Tuomo Kujala and Jukka Corander; Part V. Appendix. Mathematical background and notation John H. Williamson.
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