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Poster communications

A Bayesian Experimental Design Approach Maximizing Information Gain for Human-Computer Interaction

Abstract : A new information-theoretic approach based on Bayesian Experimental Design (BED) is applied to human-computer interaction, and in particular to multi-scale navigation. Instead of simply executing user commands, our BIG (Bayesian Information Gain) technique is modeling user behavior and tries to gain information by maximizing the expected mutual information provided by the users' subsequent input.
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Poster communications
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https://hal.inria.fr/hal-01677034
Contributor : Wanyu Liu Connect in order to contact the contributor
Submitted on : Sunday, January 7, 2018 - 6:50:50 PM
Last modification on : Wednesday, November 3, 2021 - 5:39:38 AM

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ITA_BIG_v6.pdf
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  • HAL Id : hal-01677034, version 1

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Wanyu Liu, Rafael Lucas d'Oliveira, Michel Beaudouin-Lafon, Olivier Rioul. A Bayesian Experimental Design Approach Maximizing Information Gain for Human-Computer Interaction. ITA 2017 - IEEE Information Theory and Applications Workshop, Feb 2017, San Diego, United States. pp.1. ⟨hal-01677034⟩

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