Zobrazeno 1 - 10
of 3 576
pro vyhledávání: '"Wang, Hongzhi"'
The knob tuning aims to optimize database performance by searching for the most effective knob configuration under a certain workload. Existing works suffer two significant problems. On the one hand, there exist multiple similar even useless evaluati
Externí odkaz:
http://arxiv.org/abs/2407.02803
The Spiking Neural Networks (SNNs), renowned for their bio-inspired operational mechanism and energy efficiency, mirror the human brain's neural activity. Yet, SNNs face challenges in balancing energy efficiency with the computational demands of adva
Externí odkaz:
http://arxiv.org/abs/2406.14180
Autor:
Vijayaraghavan, Prashanth, Wang, Hongzhi, Shi, Luyao, Baldwin, Tyler, Beymer, David, Degan, Ehsan
Recently, there has been a growing availability of pre-trained text models on various model repositories. These models greatly reduce the cost of training new models from scratch as they can be fine-tuned for specific tasks or trained on large datase
Externí odkaz:
http://arxiv.org/abs/2406.15476
The process of database knob tuning has always been a challenging task. Recently, database knob tuning methods has emerged as a promising solution to mitigate these issues. However, these methods still face certain limitations.On one hand, when apply
Externí odkaz:
http://arxiv.org/abs/2406.00616
Graph Neural Networks (GNNs) demonstrate excellent performance on graphs, with their core idea about aggregating neighborhood information and learning from labels. However, the prevailing challenges in most graph datasets are twofold of Insufficient
Externí odkaz:
http://arxiv.org/abs/2405.00957
Unsupervised (a.k.a. Self-supervised) representation learning (URL) has emerged as a new paradigm for time series analysis, because it has the ability to learn generalizable time series representation beneficial for many downstream tasks without usin
Externí odkaz:
http://arxiv.org/abs/2404.05057
Autor:
Jiang, Hao, Yang, Chi-yuan, Tu, Deyu, Chen, Zhu, Huang, Wei, Feng, Liang-wen, Sun, Hengda, Wang, Hongzhi, Fabiano, Simone, Zhu, Meifang, Wang, Gang
Conjugated polymer fibers can be used to manufacture various soft fibrous optoelectronic devices, significantly advancing wearable devices and smart textiles. Recently, conjugated polymer-based fibrous electronic devices have been widely used in ener
Externí odkaz:
http://arxiv.org/abs/2403.03088
Autor:
Liang, Chen, Yang, Donghua, Liang, Zhiyu, Wang, Hongzhi, Liang, Zheng, Zhang, Xiyang, Huang, Jianfeng
In recent times, the field of unsupervised representation learning (URL) for time series data has garnered significant interest due to its remarkable adaptability across diverse downstream applications. Unsupervised learning goals differ from downstr
Externí odkaz:
http://arxiv.org/abs/2312.05698
Autor:
Wong, Ken C. L., Klein, Levente, da Silva, Ademir Ferreira, Wang, Hongzhi, Singh, Jitendra, Syeda-Mahmood, Tanveer
Soil organic carbon (SOC) sequestration is the transfer and storage of atmospheric carbon dioxide in soils, which plays an important role in climate change mitigation. SOC concentration can be improved by proper land use, thus it is beneficial if SOC
Externí odkaz:
http://arxiv.org/abs/2311.13016
With the introduction of Transformers, different attention-based models have been proposed for image segmentation with promising results. Although self-attention allows capturing of long-range dependencies, it suffers from a quadratic complexity in t
Externí odkaz:
http://arxiv.org/abs/2310.04466