Zobrazeno 1 - 10
of 501
pro vyhledávání: '"Lu Zhichao"'
Publikováno v:
Communications Materials, Vol 5, Iss 1, Pp 1-19 (2024)
Abstract High-entropy alloys (HEAs) have attracted extensive attention in recent decades due to their unique chemical, physical, and mechanical properties. An in-depth understanding of the structure–property relationship in HEAs is the key to the d
Externí odkaz:
https://doaj.org/article/d177d3c5e68040eaa01913b52902216c
Automated heuristic design (AHD) has gained considerable attention for its potential to automate the development of effective heuristics. The recent advent of large language models (LLMs) has paved a new avenue for AHD, with initial efforts focusing
Externí odkaz:
http://arxiv.org/abs/2407.10873
In the realm of unsupervised image outlier detection, assigning outlier scores holds greater significance than its subsequent task: thresholding for predicting labels. This is because determining the optimal threshold on non-separable outlier score f
Externí odkaz:
http://arxiv.org/abs/2407.05382
Autor:
Shen, Shuaijie, Zhang, Rui, Wang, Chao, Huang, Renzhuo, Tuerhong, Aiersi, Guo, Qinghai, Lu, Zhichao, Zhang, Jianguo, Leng, Luziwei
Publikováno v:
J Membr Comput (2024)
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural networks(ANNs). However, the unique information propagation mechanisms and the complexity of SNN neur
Externí odkaz:
http://arxiv.org/abs/2406.12552
Anomaly synthesis is one of the effective methods to augment abnormal samples for training. However, current anomaly synthesis methods predominantly rely on texture information as input, which limits the fidelity of synthesized abnormal samples. Beca
Externí odkaz:
http://arxiv.org/abs/2404.19444
Transformer recently emerged as the de facto model for computer vision tasks and has also been successfully applied to shadow removal. However, these existing methods heavily rely on intricate modifications to the attention mechanisms within the tran
Externí odkaz:
http://arxiv.org/abs/2404.18433
As one of the emerging challenges in Automated Machine Learning, the Hardware-aware Neural Architecture Search (HW-NAS) tasks can be treated as black-box multi-objective optimization problems (MOPs). An important application of HW-NAS is real-time se
Externí odkaz:
http://arxiv.org/abs/2404.16266
Autor:
Liu, Fei, Tong, Xialiang, Yuan, Mingxuan, Lin, Xi, Luo, Fu, Wang, Zhenkun, Lu, Zhichao, Zhang, Qingfu
Heuristics are widely used for dealing with complex search and optimization problems. However, manual design of heuristics can be often very labour extensive and requires rich working experience and knowledge. This paper proposes Evolution of Heurist
Externí odkaz:
http://arxiv.org/abs/2401.02051
Autor:
Lu, Zhichao, Ding, Chuntao, Wang, Shangguang, Cheng, Ran, Juefei-Xu, Felix, Boddeti, Vishnu Naresh
Deploying high-performance convolutional neural network (CNN) models on low-earth orbit (LEO) satellites for rapid remote sensing image processing has attracted significant interest from industry and academia. However, the limited resources available
Externí odkaz:
http://arxiv.org/abs/2308.06515
Multi-task learning (MTL) seeks to learn a single model to accomplish multiple tasks by leveraging shared information among the tasks. Existing MTL models, however, have been known to suffer from negative interference among tasks. Efforts to mitigate
Externí odkaz:
http://arxiv.org/abs/2308.02066