Bayesian Methods for Interaction and Design
£34.99
- Editors:
- John H. Williamson, University of Glasgow
- Antti Oulasvirta, Aalto University, Finland
- Per Ola Kristensson, University of Cambridge
- Nikola Banovic, University of Michigan, Ann Arbor
- Date Published: August 2022
- availability: Available
- format: Paperback
- isbn: 9781108792707
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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.
Read more- Contains a wide-ranging tutorial and background chapter to familiarise readers with the ideas
- Covers a diverse array of applications
- Describes cutting-edge research
Reviews & endorsements
'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
See more reviews'A succinct and very readable account of network flow algorithms covering the classics and the latest developments. The perfect book for a course on network flow algorithms and a reference for the state of the art. It will be a frequently used addition to my bookshelf.' Kurt Mehlhorn, Max-Planck Institute for Informatics
'This high-quality book provides exhaustive references that will serve anyone deeply interested in interface design and will be helpful to those looking to get into user experience and/or the design of interfaces. … Highly recommended.' J. R. Lauber, Choice
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×Product details
- Date Published: August 2022
- format: Paperback
- isbn: 9781108792707
- length: 400 pages
- dimensions: 228 x 151 x 20 mm
- weight: 0.55kg
- availability: Available
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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