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tutorial

Bayesian Methods in Interaction Design (Tutorial)

Published: 17 March 2020 Publication History

Abstract

This tutorial introduces Bayesian computational approaches to interaction and design. Bayesian methods offer a powerful approach for interactive settings with uncertainty and noise. This course introduces the theory and practice of computational Bayesian interaction, covering inference of user data and design/adaptation of interface features based around probabilistic inference. The tutorial is built around hands-on Python programming with modern computational tools, interleaved with theory and practical examples grounded in problems of wide interest in human-computer interaction.

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cover image ACM Conferences
IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces
March 2020
153 pages
ISBN:9781450375139
DOI:10.1145/3379336
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2020

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Author Tags

  1. Bayesian
  2. filtering
  3. interaction design
  4. probabilistic

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  • Tutorial
  • Research
  • Refereed limited

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IUI '20
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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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