Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Hal Daumé"'
Autor:
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé Iii, Emma Pierson, Nihar B Shah
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0300710 (2024)
How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,000 submitting authors and 9,000 submitted papers, we surveyed the aut
Externí odkaz:
https://doaj.org/article/71cb7dcdf65a420d86a4fd1696eb9441
Publikováno v:
PLoS ONE, Vol 18, Iss 7, p e0287443 (2023)
Peer review is the backbone of academia and humans constitute a cornerstone of this process, being responsible for reviewing submissions and making the final acceptance/rejection decisions. Given that human decision-making is known to be susceptible
Externí odkaz:
https://doaj.org/article/ee45fb1c501b4aa4a109479a91f7b9b9
Autor:
Yang Trista Cao, Hal Daumé
Publikováno v:
Computational Linguistics, Vol 47, Iss 3, Pp 615-661 (2021)
AbstractCorrectly resolving textual mentions of people fundamentally entails making inferences about those people. Such inferences raise the risk of systematic biases in coreference resolution systems, including biases that can harm binary and non-bi
Externí odkaz:
https://doaj.org/article/1954163e52104379bdc123e77a08e877
Autor:
Upol Ehsan, Philipp Wintersberger, Elizabeth A Watkins, Carina Manger, Gonzalo Ramos, Justin D. Weisz, Hal Daumé Iii, Andreas Riener, Mark O Riedl
Publikováno v:
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::140a5981f8419b69ab75ee6d1492cdc1
https://doi.org/10.1145/3544549.3573832
https://doi.org/10.1145/3544549.3573832
Autor:
GEBRU, TIMNIT, MORGENSTERN, JAMIE, VECCHIONE, BRIANA, VAUGHAN, JENNIFER WORTMAN, WALLACH, HANNA, III, HAL DAUMÉ, CRAWFORD, KATE
Publikováno v:
Communications of the ACM; Dec2021, Vol. 64 Issue 12, p86-92, 7p, 1 Color Photograph
Publikováno v:
Transactions of the Association for Computational Linguistics. 10:732-745
Researchers in the social sciences are often interested in the relationship between text and an outcome of interest, where the goal is to both uncover latent patterns in the text and predict outcomes for unseen texts. To this end, this paper develops
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a36be0136bc4c2be3e844353d5f3748c
https://doi.org/10.1162/tacl_a_00487
https://doi.org/10.1162/tacl_a_00487
Autor:
Hanna Wallach, Jennifer Wortman Vaughan, Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Kate Crawford, Hal Daumé
Publikováno v:
Communications of the ACM. 64:86-92
The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dee0f9ebc19fea615df18faf56b3edb
https://doi.org/10.1145/3458723
https://doi.org/10.1145/3458723
Autor:
Amr Sharaf, Hal Daumé III
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:9541-9548
In contextual bandits, an algorithm must choose actions given ob- served contexts, learning from a reward signal that is observed only for the action chosen. This leads to an exploration/exploitation trade-off: the algorithm must balance taking actio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::234da41ec4589e1426a3e0bac974a6be
https://doi.org/10.1609/aaai.v35i11.17149
https://doi.org/10.1609/aaai.v35i11.17149
Autor:
Upol Ehsan, Philipp Wintersberger, Q. Vera Liao, Elizabeth Anne Watkins, Carina Manger, Hal Daumé III, Andreas Riener, Mark O Riedl
Publikováno v:
CHI Conference on Human Factors in Computing Systems Extended Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fd0977c48738bb97f039fb63bec0b69
https://doi.org/10.1145/3491101.3503727
https://doi.org/10.1145/3491101.3503727
Autor:
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé, Kate Crawford
Publikováno v:
Ethics of Data and Analytics ISBN: 9781003278290
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c145631803512c99d19d48de7dbaced8
https://doi.org/10.1201/9781003278290-23
https://doi.org/10.1201/9781003278290-23
