Search Results for author: Heng Qi

Found 10 papers, 3 papers with code

KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks

no code implementations22 Feb 2023 Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu

Graph neural networks for trust evaluation typically adopt a straightforward way such as one-hot or node2vec to comprehend node characteristics, which ignores the valuable semantic knowledge attached to nodes.

NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction

no code implementations4 Jul 2022 Xueyan Yin, Feifan Li, Yanming Shen, Heng Qi, BaoCai Yin

First, a spatial-temporal graph neural network is proposed, which can capture the node-specific spatial-temporal traffic patterns of different road networks.

Traffic Prediction Transfer Learning

Soft-mask: Adaptive Substructure Extractions for Graph Neural Networks

1 code implementation11 Jun 2022 Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin

Task-relevant structures can be $localized$ or $sparse$ which are only involved in subgraphs or characterized by the interactions of subgraphs (a hierarchical perspective).

Representation Learning

A New Perspective on the Effects of Spectrum in Graph Neural Networks

1 code implementation14 Dec 2021 Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, BaoCai Yin

Many improvements on GNNs can be deemed as operations on the spectrum of the underlying graph matrix, which motivates us to directly study the characteristics of the spectrum and their effects on GNN performance.

Graph Classification Graph Property Prediction +1

Federated Unlearning via Class-Discriminative Pruning

no code implementations22 Oct 2021 Junxiao Wang, Song Guo, Xin Xie, Heng Qi

Evaluated on CIFAR10 dataset, our method accelerates the speed of unlearning by 8. 9x for the ResNet model, and 7. 9x for the VGG model under no degradation in accuracy, compared to retraining from scratch.

Federated Learning Image Classification

Breaking the Expressive Bottlenecks of Graph Neural Networks

1 code implementation14 Dec 2020 Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin

Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressiveness of graph neural networks (GNNs), showing that the neighborhood aggregation GNNs were at most as powerful as 1-WL test in distinguishing graph structures.

Graph Property Prediction

Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions

no code implementations18 Apr 2020 Xueyan Yin, Genze Wu, Jinze Wei, Yanming Shen, Heng Qi, Bao-Cai Yin

The purpose of this paper is to provide a comprehensive survey on deep learning-based approaches in traffic prediction from multiple perspectives.

Traffic Prediction

An efficient deep learning hashing neural network for mobile visual search

no code implementations21 Oct 2017 Heng Qi, Wu Liu, Liang Liu

Mobile visual search applications are emerging that enable users to sense their surroundings with smart phones.

Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification

no code implementations12 Aug 2017 Yunlong Bian, Chuang Gan, Xiao Liu, Fu Li, Xiang Long, Yandong Li, Heng Qi, Jie zhou, Shilei Wen, Yuanqing Lin

Experiment results on the challenging Kinetics dataset demonstrate that our proposed temporal modeling approaches can significantly improve existing approaches in the large-scale video recognition tasks.

Action Classification General Classification +2

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