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20092023
most citedDropEdge: Towards Deep Graph Convolutional Networks on Node Classification

649 citations · 4.6k across the 115 of their papers we have counts for

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Showing 2018Show all

17 papers · 1 filter

cs.CV2018★ 62 cited

Weakly Supervised Dense Event Captioning in Videos

Xuguang Duan, Wenbing Huang, Chuang Gan +3

Dense event captioning aims to detect and describe all events of interest contained in a video. Despite the advanced development in this area, existing methods tackle this task by…

cs.LG2018★ 8 cited

An Efficient Approach to Informative Feature Extraction from Multimodal Data

Lichen Wang, Jiaxiang Wu, Shao-Lun Huang +4

One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the…

cs.CV2018★ 23 cited

Progressive Feature Alignment for Unsupervised Domain Adaptation

Chaoqi Chen, Weiping Xie, Wenbing Huang +5

Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a fully-unlabeled target domain. To tackle this task, recent approaches resort to discri…

cs.CV2018★ 160 cited

Discrimination-aware Channel Pruning for Deep Neural Networks

Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang +5

Channel pruning is one of the predominant approaches for deep model compression. Existing pruning methods either train from scratch with sparsity constraints on channels, or minimi…

stat.ML2018★ 18 cited

Hyperparameter Learning via Distributional Transfer

Ho Chung Leon Law, Peilin Zhao, Lucian Chan +2

Bayesian optimisation is a popular technique for hyperparameter learning but typically requires initial exploration even in cases where similar prior tasks have been solved. We pro…

cs.CV2018★ 13 cited

Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss

Yong Guo, Qi Chen, Jian Chen +5

Deep neural networks have exhibited promising performance in image super-resolution (SR) due to the power in learning the non-linear mapping from low-resolution (LR) images to high…