Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Anna Rumshisky"'
Publikováno v:
Translational Psychiatry, Vol 11, Iss 1, Pp 1-6 (2021)
Abstract Machine learning has been suggested as a means of identifying individuals at greatest risk for hospital readmission, including psychiatric readmission. We sought to compare the performance of predictive models that use interpretable represen
Externí odkaz:
https://doaj.org/article/5c6079f32b174790b6adfbfdcb7c94ef
Scaling up weakly-supervised datasets has shown to be highly effective in the image-text domain and has contributed to most of the recent state-of-the-art computer vision and multimodal neural networks. However, existing large-scale video-text datase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::768d155626886ffdd56a533ef378ba4e
Publikováno v:
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85f67054d851e8b43d25f7e5f2f31486
https://doi.org/10.1109/icassp43922.2022.9746975
https://doi.org/10.1109/icassp43922.2022.9746975
Publikováno v:
AAAI
University of Copenhagen
University of Copenhagen
The recent explosion in question answering research produced a wealth of both factoid reading comprehension (RC) and commonsense reasoning datasets. Combining them presents a different kind of task: deciding not simply whether information is present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a43817c440d8e6394fefbc262b0e2ca7
https://doi.org/10.1609/aaai.v34i05.6398
https://doi.org/10.1609/aaai.v34i05.6398
Autor:
Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta
Machine Learning (ML) systems are getting increasingly popular, and drive more and more applications and services in our daily life. This has led to growing concerns over user privacy, since human interaction data typically needs to be transmitted to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea31b418c7f5c35ca48651eafc097958
Publikováno v:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58fd14e725e02a7d34b10122257aa043
https://doi.org/10.18653/v1/2022.naacl-industry.7
https://doi.org/10.18653/v1/2022.naacl-industry.7
Autor:
Eric Lehman, Vladislav Lialin, Katelyn Edelwina Legaspi, Anne Janelle Sy, Patricia Therese Pile, Nicole Rose Alberto, Richard Raymund Ragasa, Corinna Victoria Puyat, Marianne Katharina Taliño, Isabelle Rose Alberto, Pia Gabrielle Alfonso, Dana Moukheiber, Byron Wallace, Anna Rumshisky, Jennifer Liang, Preethi Raghavan, Leo Anthony Celi, Peter Szolovits
Publikováno v:
Proceedings of the 4th Clinical Natural Language Processing Workshop.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca2f77725c9983974776113476cf74fb
https://doi.org/10.18653/v1/2022.clinicalnlp-1.8
https://doi.org/10.18653/v1/2022.clinicalnlp-1.8
Publikováno v:
Translational Psychiatry, Vol 11, Iss 1, Pp 1-6 (2021)
Translational Psychiatry
Translational Psychiatry
Machine learning has been suggested as a means of identifying individuals at greatest risk for hospital readmission, including psychiatric readmission. We sought to compare the performance of predictive models that use interpretable representations d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fdce01a774a0470f2b53b9528518486
https://doi.org/10.1038/s41398-020-01104-w
https://doi.org/10.1038/s41398-020-01104-w
Publikováno v:
ACL/IJCNLP (Findings)
Multiple studies have shown that Transformers are remarkably robust to pruning. Contrary to this received wisdom, we demonstrate that pre-trained Transformer encoders are surprisingly fragile to the removal of a very small number of features in the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f52f316a19e07125b5df9dd2608a1a1
https://doi.org/10.18653/v1/2021.findings-acl.300
https://doi.org/10.18653/v1/2021.findings-acl.300
Publikováno v:
J Am Med Inform Assoc
Objective The n2c2/UMass Lowell spin-off shared task focused on medical concept normalization (MCN) in clinical records. This task aimed to assess state-of-the-art methods for matching salient medical concepts from clinical records to a controlled vo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::903bc0c09f33939d33d998ed28c64e6f
https://europepmc.org/articles/PMC7647359/
https://europepmc.org/articles/PMC7647359/