{"title":"交互设计中的贝叶斯方法(教程)","authors":"John Williamson, Antti Oulasvirta, P. Kristensson","doi":"10.1145/3379336.3379354","DOIUrl":null,"url":null,"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.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bayesian Methods in Interaction Design (Tutorial)\",\"authors\":\"John Williamson, Antti Oulasvirta, P. Kristensson\",\"doi\":\"10.1145/3379336.3379354\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":335081,\"journal\":{\"name\":\"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3379336.3379354\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3379336.3379354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.