论文笔记:WSDM'22 Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation 天下客发表于Scala... 论文笔记:NeurIPS'21 Federated Graph Classification over Non-IID Graphs (GCFL) 天下客发表于FL-Gr... 论文笔记:A Survey on Graph Structure Learning: Progress and Opportunities POPO发表于图联邦学...
Knowledge distillation allows us to create small and more efficient models that retain much of the performance of their larger counterparts. Here we present a graph-based knowledge distillation framework to correctly identify and localize the document objects in a document image. Here, we design a ...
Recent work has attempted to go beyond logit-based distillation by transferring representational knowledge from the teacher to the student through the design of loss functions that align the latent embedding spaces of the teacher and student [ 31 ], see Fig.1(a) for an intuitive overview. 最近...
CL aims to learn new knowledge incrementally without forgetting prior experience, approaches which follow the taxonomy as regularization-based, replay-based and… 阅读全文 lifelong graph learning(cvpr22 oral) 论文阅读笔记: 出发点在于虽然节点数目会变化,但是图的特征数一定是固定的 Regular graph: nodes...
Graph Neural Networks (GNNs) have excelled in various graph-based applications. Recently, knowledge distillation (KD) has provided a new approach to further boost GNNs performance. However, in the KD process, the GNN student may encounter noise issues while learning from GNN teacher and input gra...
这篇文章是基于传统KD的改进版,类似于同样发表在CVPR2019的Relational Knowledge Distillation。主要想解决的问题是Knowledge Distillation(KD)中knowledge如何定义的问题,传统的做法仅仅使用logits作为知识,将学生和老师的对于单个sample的logits进行逼近(比如阿里AAAI2019的Rocket Launching)。但是知识不应该只局限于约束单个sampl...
FedACK: A federated social bot detection method that proposes a GAN-based federated adversarial comparison knowledge distillation mechanism. The relationship information between users is not considered in the social bot detection model, and the detection performance has a large gap with the detection of...
DGL-LifeSci: a DGL-based package for various applications in life science with graph neural networks.https://github.com/awslabs/dgl-lifesci DGL-KE: a high performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.https://github.com/awslabs/dgl-ke ...
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Boosting Graph Neural Networks via Adaptive Knowledge Distillation摘要图神经网络(GNN)在各种图挖掘任务上表现出卓越的性能。研究表明,在共享相同的消息传递框架下,不同GNN可以从相同的图中学习不同的知识…