Zobrazeno 1 - 10
of 2 147
pro vyhledávání: '"Lee, So‐Lun"'
Multimodal incremental learning needs to digest the information from multiple modalities while concurrently learning new knowledge without forgetting the previously learned information. There are numerous challenges for this task, mainly including th
Externí odkaz:
http://arxiv.org/abs/2412.09549
While large vision-language models (LVLMs) have shown impressive capabilities in generating plausible responses correlated with input visual contents, they still suffer from hallucinations, where the generated text inaccurately reflects visual conten
Externí odkaz:
http://arxiv.org/abs/2412.06775
Financial assets exhibit complex dependency structures, which are crucial for investors to create diversified portfolios to mitigate risk in volatile financial markets. To explore the financial asset dependencies dynamics, we propose a novel approach
Externí odkaz:
http://arxiv.org/abs/2406.11886
Volatility, as a measure of uncertainty, plays a crucial role in numerous financial activities such as risk management. The Econometrics and Machine Learning communities have developed two distinct approaches for financial volatility forecasting: the
Externí odkaz:
http://arxiv.org/abs/2402.06642
Product disassembly plays a crucial role in the recycling, remanufacturing, and reuse of end-of-use (EoU) products. However, the current manual disassembly process is inefficient due to the complexity and variation of EoU products. While fully automa
Externí odkaz:
http://arxiv.org/abs/2310.13643
In this paper, we tackle two challenges in multimodal learning for visual recognition: 1) when missing-modality occurs either during training or testing in real-world situations; and 2) when the computation resources are not available to finetune on
Externí odkaz:
http://arxiv.org/abs/2303.03369
Autor:
Lee, Wei Lun1 (AUTHOR) weilunlee1988@gmail.com, Alias, Azmi1 (AUTHOR), Lim, Mei Sin1 (AUTHOR)
Publikováno v:
Asian Journal of Neurosurgery. Dec2024, Vol. 19 Issue 4, p816-824. 9p.
Traditional recommender systems are typically passive in that they try to adapt their recommendations to the user's historical interests. However, it is highly desirable for commercial applications, such as e-commerce, advertisement placement, and ne
Externí odkaz:
http://arxiv.org/abs/2211.10002
Autor:
Chuang, Hsiao-Chi a, b, 1, Chang, Jer-Hwa a, c, d, 1, Fan, Yen-Yi e, Hsieh, Chia-Ling f, Lee, Yueh-Lun e, g, h, ⁎
Publikováno v:
In Biomedicine & Pharmacotherapy December 2024 181
Autor:
Chuang, Hsiao-Chi, Chuang, Kai-Jen, Cheng, Po-Ching, Hsieh, Chia-Ling, Fan, Yen-Yi, Lee, Yueh-Lun
Publikováno v:
In Phytomedicine December 2024 135