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pro vyhledávání: '"Lee Ivan"'
Recent studies have highlighted significant fairness issues in Graph Transformer (GT) models, particularly against subgroups defined by sensitive features. Additionally, GTs are computationally intensive and memory-demanding, limiting their applicati
Externí odkaz:
http://arxiv.org/abs/2412.10669
Publikováno v:
(2024) Engineering Applications of Artificial Intelligence, 136, 109030
Recent advancements in deep convolutional neural networks have significantly improved the performance of saliency prediction. However, the manual configuration of the neural network architectures requires domain knowledge expertise and can still be t
Externí odkaz:
http://arxiv.org/abs/2407.20062
Scientific collaboration is a significant behavior in knowledge creation and idea exchange. To tackle large and complex research questions, a trend of team formation has been observed in recent decades. In this study, we focus on recognizing collabor
Externí odkaz:
http://arxiv.org/abs/2406.06617
What is the relationship between model architecture and the ability to perform in-context learning? In this empirical study, we take the first steps toward answering this question. We evaluate thirteen model architectures capable of causal language m
Externí odkaz:
http://arxiv.org/abs/2310.08049
Automated multi-label chest X-rays (CXR) image classification has achieved substantial progress in clinical diagnosis via utilizing sophisticated deep learning approaches. However, most deep models have high computational demands, which makes them le
Externí odkaz:
http://arxiv.org/abs/2305.06244
Publikováno v:
Journal of Biomedical Informatics 130 (2022): 104092
Named Entity Recognition (NER) or the extraction of concepts from clinical text is the task of identifying entities in text and slotting them into categories such as problems, treatments, tests, clinical departments, occurrences (such as admission an
Externí odkaz:
http://arxiv.org/abs/2208.13949
Publikováno v:
In Government Information Quarterly December 2024 41(4)
Autor:
Manuel, Douglas G. a, b, ⁎, Saran, Gauri a, Lee, Ivan a, Yusuf, Warsame g, Thomson, Mathew a, Mercier, Élisabeth b, Pileggi, Vince h, McKay, R. Michael c, Corchis-Scott, Ryland c, Geng, Qiudi c, Servos, Mark d, Ikert, Heather d, Dhiyebi, Hadi d, Yang, Ivy M. e, Harvey, Bart f, Rodenburg, Erin f, Millar, Catherine i, Delatolla, Robert b
Publikováno v:
In Science of the Total Environment 1 November 2024 949
Autor:
Chi Tran, Linh a, Hong Nguyen, Huynh a, Su, Xiao a, Dai, Jiabin a, Lee, Ivan a, Losic, Dusan b, c, Meng, Qingshi d, Kuan, Hsu-Chiang e, Ma, Jun a
Publikováno v:
In Applied Surface Science 1 February 2025 681
In the age of social computing, finding interesting network patterns or motifs is significant and critical for various areas such as decision intelligence, intrusion detection, medical diagnosis, social network analysis, fake news identification, nat
Externí odkaz:
http://arxiv.org/abs/2204.02676