Temporal Relation Regularization. 这篇论文和论文:Deep Reinforcement Learning with Relational Inductive Biases. 都用到了图网络和强化学习的结合,都提到了relational reinforcement learning 这个概念。有机会可以了解一下。
Graph Convolutional Reinforcement Learning for Collaborative Queuing Agents In this paper, we explore the use of multi-agent deep learning as well as learning to cooperate principles to meet stringent service level agreements, in t... H Fawaz,J Lesca,PTA Quang,... - arXiv e-prints 被引量: ...
A. Aspuru-Guzik, R. P. Adams, Convolutional Networks on Graphs for Learning Molecular Fingerprints...
Graph convolutional networkReinforcement learningTo achieve high quality of service for computation-intensive applications, multi-access edge computing (MEC) is proposed for offloading tasks to MEC servers. The emerging reinforcement learning-based task offloading strategies have attracted attention of ...
portfolio management reinforcement learning graph convolutional network company relationshipCited by (0)Si Shi received the B.S. degree in information management (2014) and the M.S. degree in management information systems (2017) from Zhongnan University of Economics and Law, Wuhan, China. She is ...
图卷积网络(Graph Convolutional Networks, GCNs)总结如Table 3所示,其中一类图卷积网络可详见:图卷积网络。 卷积操作 谱方法 卷积是卷积神经网络CNNs中最基本的操作,但是由于图不具备网格结构,针对图像和文本的标准卷积并能够直接应用于图。Bruna等首先从谱域中使用图的拉普拉斯矩阵 ...
Graph Convolutional Neural Networks教程:https://tkipf.github.io/graph-convolutional-networks/ 5. Videos as Space-Time Region Graphs 这篇由卡耐基梅隆大学(CMU)的王小龙发表的,把video表达成为一个roi proposal组成的graph,在上面定义local和nonlocal edges,做graph convolution。
【导读】图卷积网络(Graph Convolutional Network,GCN)是近年来逐渐流行的一种神经网络结构。不同于只能用于网格结构(grid-based)数据的传统网络模型 LSTM 和 CNN,图卷积网络能够处理具有广义拓扑图结构的数据,并深入发掘其特征和规律,例如 PageRank 引用网络、社交网络、通信网络、蛋白质分子结构等一系列具有空间拓扑图...
Graph Convolutional Neural Networks教程:https://tkipf.github.io/graph-convolutional-networks/ 5. Videos as Space-Time Region Graphs 这篇由卡耐基梅隆大学(CMU)的王小龙发表的,把video表达成为一个roi proposal组成的graph,在上面定义local和nonlocal edges,做graph convolution。
(CSOs). To this end, in this paper, we propose a Multi-Agent Graph Convolutional Reinforcement Learning (MAGC) framework to enable CSOs to achieve more effective use of these stations by providing dynamic pricing for each of the continuously arising charging requests with optimizing multiple long...