Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Han, SungWon"'
The spread of fake news negatively impacts individuals and is regarded as a significant social challenge that needs to be addressed. A number of algorithmic and insightful features have been identified for detecting fake news. However, with the recen
Externí odkaz:
http://arxiv.org/abs/2406.11260
Autor:
Han, Sungwon, Ahn, Donghyun, Lee, Seungeon, Song, Minhyuk, Park, Sungwon, Park, Sangyoon, Kim, Jihee, Cha, Meeyoung
Moving beyond traditional surveys, combining heterogeneous data sources with AI-driven inference models brings new opportunities to measure socio-economic conditions, such as poverty and population, over expansive geographic areas. The current resear
Externí odkaz:
http://arxiv.org/abs/2406.09799
The increasing frequency and intensity of natural disasters demand more sophisticated approaches for rapid and precise damage assessment. To tackle this issue, researchers have developed various methods on disaster benchmark datasets from satellite i
Externí odkaz:
http://arxiv.org/abs/2406.08020
Federated learning combines local updates from clients to produce a global model, which is susceptible to poisoning attacks. Most previous defense strategies relied on vectors derived from projections of local updates on a Euclidean space; however, t
Externí odkaz:
http://arxiv.org/abs/2404.11905
Large Language Models (LLMs), with their remarkable ability to tackle challenging and unseen reasoning problems, hold immense potential for tabular learning, that is vital for many real-world applications. In this paper, we propose a novel in-context
Externí odkaz:
http://arxiv.org/abs/2404.09491
Autor:
Park, Sungkyu, Han, Sungwon, Kim, Jeongwook, Molaie, Mir Majid, Vu, Hoang Dieu, Singh, Karandeep, Han, Jiyoung, Lee, Wonjae, Cha, Meeyoung
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 3, p e28926 (2021)
Externí odkaz:
https://doaj.org/article/8e96cbe5ad3d43e1ae057b28080730af
Publikováno v:
JMIR mHealth and uHealth, Vol 7, Iss 12, p e14473 (2019)
BackgroundAs societies become more complex, larger populations suffer from insomnia. In 2014, the US Centers for Disease Control and Prevention declared that sleep disorders should be dealt with as a public health epidemic. However, it is hard to pro
Externí odkaz:
https://doaj.org/article/f839eadb52f24b9ba5fc6c4e99d99dec
Federated learning is used to train a shared model in a decentralized way without clients sharing private data with each other. Federated learning systems are susceptible to poisoning attacks when malicious clients send false updates to the central s
Externí odkaz:
http://arxiv.org/abs/2308.09318
Federated learning enables learning from decentralized data sources without compromising privacy, which makes it a crucial technique. However, it is vulnerable to model poisoning attacks, where malicious clients interfere with the training process. P
Externí odkaz:
http://arxiv.org/abs/2307.09048
Autor:
Han, Sungwon, Lee, Seungeon, Wu, Fangzhao, Kim, Sundong, Wu, Chuhan, Wang, Xiting, Xie, Xing, Cha, Meeyoung
Algorithmic fairness has become an important machine learning problem, especially for mission-critical Web applications. This work presents a self-supervised model, called DualFair, that can debias sensitive attributes like gender and race from learn
Externí odkaz:
http://arxiv.org/abs/2303.08403