In recent years, emerging self-supervised learning provides a potential solution to address the aforementioned problems. However, existing self-supervised works also operate on the complete graph data and are biased to fit either global or very local (1-hop neighborhood) graph structures in defining...
Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning 动机 图表示学习最近引起了很多关注。由于有限的计算和内存成本,现有的以完整图数据为基础的图神经网络不可扩展。因此,在大规模图数据中捕获丰富的信息
论文标题:Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning论文作者:Yizhu Jiao, Yun Xiong, Jiawei Zhang, Yao Zhang, Tianqi Zhang, Yangyong Zhu论文来源:2020 ICDM论文地址:download 论文代码:download 1 Introduction 创新点:提出一种新的子图对比度自监督表示学习方法,利用中心节点...
Graph-based semi-supervised learning (SSL) has been widely investigated in recent works considering its powerful ability to naturally incorporate the diverse types of information and measurements. However, traditional graph-based SSL methods have cubic complexities and leading to low scalability. In this...
Here we show that self-supervised deep learning can be leveraged to search for and retrieve WSIs at speeds that are independent of repository size. The algorithm, which we named SISH (for self-supervised image search for histology) and provide as an open-source package, requires only slide-...
A scalable graph-based semi-supervised learning approach is proposed.It extends the concept of graph topology imbalance to large datasets.It integrates the weights of the labeled samples into the unified semi-supervised model.It provides the anchor labels, the affinity graph and a linear mapping.Per...
In this paper, we propose a semi-supervised Multi-Graph Hashing (MGH) approach for scalable similarity search. Different form the traditional methods, our approach can effectively integrate the multiple modalities with optimized weights in a multi-graph learning framework. In this way, the effects ...
deep learning, and multimedia search. His representative works include deep high-resolution network (HRNet), discriminative regional feature integration (DRFI) for supervised saliency detection, neighborhood graph search (NGS, SPTAG) fo...
Deep learning with coherent VCSEL neural networks Article17 July 2023 Introduction Machine learning has become ubiquitous in modern data analysis, decision-making, and optimization. A prominent subset of machine learning is the artificial deep neural network (DNN), which has revolutionized many fields,...
@inproceedings{ wu2023difformer,title={{DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion},author={Qitian Wu and Chenxiao Yang and Wentao Zhao and Yixuan He and David Wipf and Junchi Yan},booktitle={International Conference on Learning Representations (ICLR)},year={...