Zobrazeno 1 - 10
of 432
pro vyhledávání: '"Leung, Cheuk"'
We present a functional generative approach to extract risk-neutral densities from market prices of options. Specifically, we model the log-returns on the time-to-maturity continuum as a stochastic curve driven by standard normal. We then use neural
Externí odkaz:
http://arxiv.org/abs/2405.17770
The growing demand for personalized decision-making has led to a surge of interest in estimating the Conditional Average Treatment Effect (CATE). Various types of CATE estimators have been developed with advancements in machine learning and causal in
Externí odkaz:
http://arxiv.org/abs/2402.18392
Vision Transformers (ViTs) are increasingly used in computer vision due to their high performance, but their vulnerability to adversarial attacks is a concern. Existing methods lack a solid theoretical basis, focusing mainly on empirical training adj
Externí odkaz:
http://arxiv.org/abs/2402.03317
Autor:
Li, Yijun, Leung, Cheuk Hang, Sun, Xiangqian, Wang, Chaoqun, Huang, Yiyan, Yan, Xing, Wu, Qi, Wang, Dongdong, Huang, Zhixiang
Consumer credit services offered by e-commerce platforms provide customers with convenient loan access during shopping and have the potential to stimulate sales. To understand the causal impact of credit lines on spending, previous studies have emplo
Externí odkaz:
http://arxiv.org/abs/2312.10388
Accurate segmentation of surgical instrument tip is an important task for enabling downstream applications in robotic surgery, such as surgical skill assessment, tool-tissue interaction and deformation modeling, as well as surgical autonomy. However,
Externí odkaz:
http://arxiv.org/abs/2309.00957
Multivariate sequential data collected in practice often exhibit temporal irregularities, including nonuniform time intervals and component misalignment. However, if uneven spacing and asynchrony are endogenous characteristics of the data rather than
Externí odkaz:
http://arxiv.org/abs/2306.09147
Autor:
Ma, Shumin, Yuan, Zhiri, Wu, Qi, Huang, Yiyan, Hu, Xixu, Leung, Cheuk Hang, Wang, Dongdong, Huang, Zhixiang
Classical Domain Adaptation methods acquire transferability by regularizing the overall distributional discrepancies between features in the source domain (labeled) and features in the target domain (unlabeled). They often do not differentiate whethe
Externí odkaz:
http://arxiv.org/abs/2305.19499
Autor:
Chan, Ming Chiu1 (AUTHOR), Leung, Cheuk Cheung Derek1 (AUTHOR) lcc487@ha.org.hk, Chan, Yu Hong1 (AUTHOR), Ho, Man Ying1 (AUTHOR), Chen, Chun Hoi1 (AUTHOR), Ngai, Ching Man1 (AUTHOR), Chan, Hiu Ching Christy1 (AUTHOR), Yeung, Yiu Cheong1 (AUTHOR), Koizumi, Tomonobu1 (AUTHOR) tomonobu@shinshu-u.ac.jp
Publikováno v:
Case Reports in Pulmonology. 10/15/2024, Vol. 2024, p1-5. 5p.
Estimating the average treatment effect (ATE) from observational data is challenging due to selection bias. Existing works mainly tackle this challenge in two ways. Some researchers propose constructing a score function that satisfies the orthogonal
Externí odkaz:
http://arxiv.org/abs/2209.01956
Autor:
Huang, Yiyan, Leung, Cheuk Hang, Yan, Xing, Wu, Qi, Ma, Shumin, Yuan, Zhiri, Wang, Dongdong, Huang, Zhixiang
Many practical decision-making problems in economics and healthcare seek to estimate the average treatment effect (ATE) from observational data. The Double/Debiased Machine Learning (DML) is one of the prevalent methods to estimate ATE in the observa
Externí odkaz:
http://arxiv.org/abs/2209.01805