Zobrazeno 1 - 10
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pro vyhledávání: '"Park, JaeYoung"'
The recent huge advance of Large Language Models (LLMs) is mainly driven by the increase in the number of parameters. This has led to substantial memory capacity requirements, necessitating the use of dozens of GPUs just to meet the capacity. One pop
Externí odkaz:
http://arxiv.org/abs/2403.06664
Biased data can lead to unfair machine learning models, highlighting the importance of embedding fairness at the beginning of data analysis, particularly during dataset curation and labeling. In response, we propose Falcon, a scalable fair active lea
Externí odkaz:
http://arxiv.org/abs/2401.12722
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 1, p e17782 (2021)
BackgroundPatient portals have drawn much attention, as they are considered an important tool for health providers in facilitating patient engagement. However, little is known about whether the intensive use of patient portals contributes to improved
Externí odkaz:
https://doaj.org/article/e3ee730c462f4cf5bd82e10ff8309e3d
Channel sounding is essential for the development of radio systems. One flexible strategy is the switched-array-based channel sounding, where antenna elements are activated at different time instants to measure the channel spatial characteristics. Al
Externí odkaz:
http://arxiv.org/abs/2304.10662
Patient-reported outcome (PRO) measures are increasingly collected as a means of measuring healthcare quality and value. The capability to predict such measures enables patient-provider shared decision making and the delivery of patient-centered care
Externí odkaz:
http://arxiv.org/abs/2210.09362
As machine learning becomes prevalent, mitigating any unfairness present in the training data becomes critical. Among the various notions of fairness, this paper focuses on the well-known individual fairness, which states that similar individuals sho
Externí odkaz:
http://arxiv.org/abs/2209.07047
Autor:
Park, Jaeyoung, Pham, Hoang Giang, Kim, Jongchan, Nguyen, Quang Khanh, Cho, Sangho, Sung, Myung Mo
Publikováno v:
In Applied Surface Science 15 June 2024 658
Publikováno v:
In Safety and Health at Work March 2024 15(1):1-8
Autor:
Park, Jaeyoung, Zhong, Xiang, Miley, Emilie N., Rutledge, Rachel S., Kakalecik, Jaquelyn, Johnson, Matthew C., Gray, Chancellor F.
Publikováno v:
In Arthroplasty Today February 2024 25
Correlated outcomes are common in many practical problems. In some settings, one outcome is of particular interest, and others are auxiliary. To leverage information shared by all the outcomes, traditional multi-task learning (MTL) minimizes an avera
Externí odkaz:
http://arxiv.org/abs/2011.05493