Mémento S.A.R.L.Business Directories,Company Directories

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Company Address:	54, Rte de Paris,77930 Chailly en Bière,,France
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HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage . . .
To address these issues, we develop HGCN2SP, a novel model with a hierarchical graph designed for 2SP problems, encoding each scenario and modeling their relationships hierarchically The model is trained in a reinforcement learning paradigm to utilize the feedback of the solver
ICML 2024 | 最高提速1440倍！中科院自动化所15秒用GCN搞定随机规划-CSDN博客
其中，两阶段随机规划（Two-Stage Stochastic Programming, 2SP）作为建模此类决策问题的有效方法，应用十分广泛。中科院自动化所的这项成果——HGCN2SP 模型（HGCN 代表分层图卷积网络），正是将 2SP 方法与图卷积网络结合，利用模型更高效地实现了此类问题求解。
HGCN2SP | Proceedings of the 41st International Conference on Machine . . .
To address these issues, we develop HGCN2SP, a novel model with a hierarchical graph designed for 2SP problems, encoding each scenario and modeling their relationships hierarchically The model is trained in a reinforcement learning paradigm to utilize the feedback of the solver
HGCN2SP README. md at main · samwu-learn HGCN2SP - GitHub
HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming - samwu-learn HGCN2SP
HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage . . .
Two-stage Stochastic Programming (2SP) is a powerful framework for modeling decision-making under uncertainty 1 Institute of Automation, Chinese Academy of Sciences,
2024国际机器学习大会（ICML）自动化所入选成果速览
我们提出了hgcn2sp模型，该模型利用层次化图卷积网络提取场景的表征，采用基于注意力机制的解码器挑选代表性的场景，并结合强化学习（rl）优化其选择，实现了2sp问题的高效求解。在设施选址问题上的实验表明，hgcn2sp能够做出比现有方法更优的决策。
HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage . . .
hgcn2sp是一个创新的框架，结合了层次化图卷积网络和强化学习方法，用于解决两阶段随机规划问题。本项目聚焦于cflp，通过学习场景特征，实现高效的求解。
比传统方法快 1440 倍！中科院 HGCN2SP 模型入选 ICML 2024
该研究的核心是 hgcn2sp 模型，它将两阶段随机规划（2sp）方法与图卷积网络结合，在条件不确定的情况下实现了高效决策。随机规划是一种在数学领域广泛应用的技术，用于解决在不确定条件下的决策问题。
最高提速1440倍！15秒用GCN搞定随机规划，中科院自动化所新成果入选ICML 24
研究团队针对两阶段随机规划问题求解，提出了基于层次化图卷积网络的hgcn2sp模型。具体的在算法设计方面，团队通过构建层次图来表征2SP问题，其中底层的图用来表征每个场景的特性，而顶层的图则用于表征场景之间的关系。
HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage . . .
The policy network is equipped with a hierarchical graph convolutional network for feature encoding and an attention-based decoder for scenario selection in proper order Evaluation of two classic 2SP problems demonstrates that HGCN2SP provides high-quality decisions in a short computational time