论文阅读13-SCGC:Simple Contrastive Graph Clustering 存在的问题 由于对比学习的发展,设计了更加一致和有辨别力的对比损失函数来取代网络训练的聚类引导损失函数。结果,缓解了手动试错问题,并提高了聚类性能。然而,复杂的数据增强和耗时的图卷积操作降低了这些方法的
论文标题:Deep Graph Clustering via Dual Correlation Reduction论文作者:Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton论文来源:2020, ICML论文地址:download 论文代码:download 1 介绍本文主要介绍 SimCLR框架。定义:SimCLR:一个简单的视觉表示对比学习框架,不仅比以前的工作更出色,而且也更简单,...
论文阅读“Simple Contrastive Graph Clustering” Liu Y, Yang X, Zhou S, et al. Simple Contrastive Graph Clustering[J]. arXiv preprint arXiv:2205.07865, 2022. 摘要导读 复杂的数据增强( complicated data augmentations)和较为耗时的图卷积操作(time-consuming graph convolutional operation)影响了对比学习在...
Long - Form Video - Language Pre -Training with Multimodal Temporal Contrastive Learning 2664 18:00 EvenNet: lgnoring Odd - Hop Neighbors Improves Robustness of Graph Neural Networks 2662 17:00 BMU - MoCo: Bidirectional Momentum Update for Continual Video - Language Modeling 2664 18:00 重新审视...
(3) where SiB ∈ Rp2×k×t is the constructed 3-D tensor via the non-local clustering of a sub-cubic ui ∈ Rp×p×t [3], p and k are the spatial size and number of the sub-cubic respectively, Qi ∈ Rd×t(d t) is an orthogonal subspace projection ...
natural language processing;knowledge graph completion;prompt learning;positive unlabeled learning 1. Introduction Large-scale knowledge graphs such as FreeBase [1], YAGO [2], and DBpedia [3] have been instrumental in supporting various artificial intelligence systems. These systems include semantic searc...