Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Goh, Sim Kuan"'
Autor:
Du, Guodong, Lee, Junlin, Li, Jing, Jiang, Runhua, Guo, Yifei, Yu, Shuyang, Liu, Hanting, Goh, Sim Kuan, Tang, Ho-Kin, He, Daojing, Zhang, Min
While fine-tuning pretrained models has become common practice, these models often underperform outside their specific domains. Recently developed model merging techniques enable the direct integration of multiple models, each fine-tuned for distinct
Externí odkaz:
http://arxiv.org/abs/2410.02396
Drawing inspiration from the philosophy of Yi Jing, the Yin-Yang pair optimization (YYPO) algorithm has been shown to achieve competitive performance in single objective optimizations, in addition to the advantage of low time complexity when compared
Externí odkaz:
http://arxiv.org/abs/2408.05564
Autor:
Du, Guodong, Jiang, Runhua, Yang, Senqiao, Li, Haoyang, Chen, Wei, Li, Keren, Goh, Sim Kuan, Tang, Ho-Kin
Darwinian evolution of the biological brain is documented through multiple lines of evidence, although the modes of evolutionary changes remain unclear. Drawing inspiration from the evolved neural systems (e.g., visual cortex), deep learning models h
Externí odkaz:
http://arxiv.org/abs/2408.05563
Neural architecture search (NAS) automates neural network design by using optimization algorithms to navigate architecture spaces, reducing the burden of manual architecture design. While NAS has achieved success, applying it to emerging domains, suc
Externí odkaz:
http://arxiv.org/abs/2408.05556
Autor:
Du, Guodong, Li, Jing, Liu, Hanting, Jiang, Runhua, Yu, Shuyang, Guo, Yifei, Goh, Sim Kuan, Tang, Ho-Kin
Fine-tuning pre-trained language models, particularly large language models, demands extensive computing resources and can result in varying performance outcomes across different domains and datasets. This paper examines the approach of integrating m
Externí odkaz:
http://arxiv.org/abs/2406.12208
Spiking neural networks (SNNs) have gained prominence for their potential in neuromorphic computing and energy-efficient artificial intelligence, yet optimizing them remains a formidable challenge for gradient-based methods due to their discrete, spi
Externí odkaz:
http://arxiv.org/abs/2406.02349
Autor:
Tang, Ho-Kin, Goh, Sim Kuan
Drawing inspiration from the philosophy of Yi Jing, Yin-Yang pair optimization (YYPO) has been shown to achieve competitive performance in single objective optimizations. Besides, it has the advantage of low time complexity when comparing to other po
Externí odkaz:
http://arxiv.org/abs/2104.08564
Approach and landing accidents have resulted in a significant number of hull losses worldwide. Technologies (e.g., instrument landing system) and procedures (e.g., stabilized approach criteria) have been developed to reduce the risks. In this paper,
Externí odkaz:
http://arxiv.org/abs/2011.09335
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