Search Results for author: Zedong Tang

Found 7 papers, 3 papers with code

Neural Gaussian Similarity Modeling for Differential Graph Structure Learning

no code implementations15 Dec 2023 Xiaolong Fan, Maoguo Gong, Yue Wu, Zedong Tang, Jieyi Liu

Graph Structure Learning (GSL) has demonstrated considerable potential in the analysis of graph-unknown non-Euclidean data across a wide range of domains.

Graph structure learning

Evolutionary Multitasking with Solution Space Cutting for Point Cloud Registration

no code implementations12 Dec 2022 Wu Yue, Peiran Gong, Maoguo Gong, Hangqi Ding, Zedong Tang, Yibo Liu, Wenping Ma, Qiguang Miao

However, most evolving registration methods cannot tackle the local optimum well and they have rarely investigated the success ratio, which implies the probability of not falling into local optima and is closely related to the practicality of the algorithm.

Point Cloud Registration Transfer Learning

SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature

1 code implementation CVPR 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

SKFAC:Training Neural Networks with Faster Kronecker-Factored Approximate Curvature

1 code implementation Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

AsymptoticNG: A regularized natural gradient optimization algorithm with look-ahead strategy

no code implementations24 Dec 2020 Zedong Tang, Fenlong Jiang, Junke Song, Maoguo Gong, Hao Li, Fan Yu, Zidong Wang, Min Wang

Optimizers that further adjust the scale of gradient, such as Adam, Natural Gradient (NG), etc., despite widely concerned and used by the community, are often found poor generalization performance, compared with Stochastic Gradient Descent (SGD).

Locality Preserving Dense Graph Convolutional Networks with Graph Context-Aware Node Representations

1 code implementation12 Oct 2020 Wenfeng Liu, Maoguo Gong, Zedong Tang, A. K. Qin

To enhance node representativeness, the output of each convolutional layer is concatenated with the output of the previous layer's readout to form a global context-aware node representation.

General Classification Graph Classification +1

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