Zobrazeno 1 - 10
of 144
pro vyhledávání: '"Jeffrey Heer"'
Publikováno v:
EPJ Data Science, Vol 11, Iss 1, Pp 1-26 (2022)
Abstract Large scale analysis of source code, and in particular scientific source code, holds the promise of better understanding the data science process, identifying analytical best practices, and providing insights to the builders of scientific to
Externí odkaz:
https://doaj.org/article/a93f758ee86046299b5d7d2ac973c425
Autor:
Jeffrey Heer
Publikováno v:
Harvard Data Science Review (2021)
Externí odkaz:
https://doaj.org/article/f0c93156f1ce434cab35ad1171fe4634
The in-context learning capabilities of LLMs like GPT-3 allow annotators to customize an LLM to their specific tasks with a small number of examples. However, users tend to include only the most obvious patterns when crafting examples, resulting in u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d3dd0df0e6225e1dc29424acf6f653f
Autor:
Jon E. Froehlich, Siddhant Patil, Devanshi Chauhan, Manaswi Saha, Jeffrey Heer, Rachel Kangas
Publikováno v:
Proceedings of the ACM on Human-Computer Interaction. 4:1-26
Traditionally, urban accessibility is defined as the ease of reaching destinations. Studies on urban accessibility for pedestrians with mobility disabilities (e.g., wheelchair users) have primarily focused on understanding the challenges that the bui
Autor:
Manaswi Saha, Siddhant Patil, Emily Cho, Evie Yu-Yen Cheng, Chris Horng, Devanshi Chauhan, Rachel Kangas, Richard McGovern, Anthony Li, Jeffrey Heer, Jon E. Froehlich
Publikováno v:
CHI Conference on Human Factors in Computing Systems.
Publikováno v:
UIST
Interactive articles are an effective medium of communication in education, journalism, and scientific publishing, yet are created using complex general-purpose programming tools. We present Idyll Studio, a structured editor for authoring and publish
Autor:
Jeffrey Heer
Publikováno v:
2021 IEEE Visualization Conference (VIS).
Publikováno v:
ACM Transactions on Computer-Human Interaction. 26:1-27
Tools for Interactive Machine Learning (IML) enable end users to update models in a “rapid, focused, and incremental”—yet local—manner. In this work, we study the question of local decision making in an IML context around feature selection fo
Autor:
Leilani Battle, Jeffrey Heer
Publikováno v:
Computer Graphics Forum. 38:145-159
Publikováno v:
Computer Graphics Forum. 38:541-551