[引用][C] Graph Neural Networks: A Review of Methods and Applications (圖神經網絡: 方法與應用綜述)

J Zhou, G Cui, Z Zhang, C Yang, Z Liu, L Wang, C Li…

[引用][C] Graph Neural Networks: A Review of Methods and Applications (图神经网络: 方法与应用综述)

J Zhou, G Cui, Z Zhang, C Yang, Z Liu, L Wang, C Li…

内存制约加速比模型及其对计算的影响

孙贤和, 鲁潇阳 - 计算机科学技术学报, 2023 - jcst.ict.ac.cn
… Range comparison compares the performance of programs … the roads from A to B, make a
graph based on the road-map, and … the data processing needs of deep learning[59], and ASIC …

基于问题特征的需求工程问题难度分析

Z Ren, H Jiang, J Xuan, S Zhang, Z Luo - Science China Information …, 2017 - Springer
… Then in the second stage, we analyze the instances … as meta-data in the machine learning
community [8], which are … for other problem domains that have graph based or vector based …

利用遺傳程式設計從專家示範自動推論任務子結構

劉容均 - 2023 - tdr.lib.ntu.edu.tw
… differs from deep learning, as it offers flexibility in generating models or programs with domain-…
In this section, we analyze the output of each process in the induction module and training …

[PDF][PDF] 编译优化序列选择研究进展

高国军, 任志磊, 张静宣, 李晓晨… - Chinese Science …, 2011 - csjxzhang.github.io
… Feature mining for machine learning based compilation optimization. … A graph-based iterative
compiler pass selection and phase … of good optimization sequences for programs remains …

在需求與供應不確定下自行車共享系統多站點間之供需媒合

于妙善 - 臺灣大學工業工程學研究所學位論文, 2017 - airitilibrary.com
… We present an analysis of the … programming model to obtain the optimal dispatch quantity
and transfer between pair of station of supply and demand. Finally, we apply deep learning

單一與集成特徵選取方法於高維度資料之比較

YT Sung - 2019 - ir.lib.ncu.edu.tw
… Components Analysis, PCA),引用集成學習的中序列式集成和並列式集成的概念形成序列式
集成特徵選取和並列式集成特徵選取,最後利用分類正確率,F1-Score 以及執行時間來衡量特徵選取…

[引用][C] 基於深度學習與語義提取之自動化韌體漏洞檢測系統

王子菁

基于图特征的组织病理学图像分析方法的最新发展情况与展望

何睿琳, 杨欣怡, 孙洪赞, 李晨 - 数据与计算发展前沿, 2024 - jfdc.cnic.cn
machine learning technologies has shown strong potential in histopathological image analysis.
… A scalable graph-based framework for multi-organ histology image classification[J]. IEEE …