103 citations · 360 across the 124 of their papers we have counts for
9 papers · 1 filter
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge
Yaxin Luopan, Rui Han, Qinglong Zhang +2
Deep Neural Networks (DNNs) have been ubiquitously adopted in internet of things and are becoming an integral of our daily life. When tackling the evolving learning tasks in real w…
HiTailor: Interactive Transformation and Visualization for Hierarchical Tabular Data
Guozheng Li, Runfei Li, Zicheng Wang +3
Tabular visualization techniques integrate visual representations with tabular data to avoid additional cognitive load caused by splitting users' attention. However, most of the ex…
Robust Knowledge Adaptation for Dynamic Graph Neural Networks
Hanjie Li, Changsheng Li, Kaituo Feng +3
Graph structured data often possess dynamic characters in nature. Recent years have witnessed the increasing attentions paid to dynamic graph neural networks for modelling graph da…
Blind Face Restoration: Benchmark Datasets and a Baseline Model
Puyang Zhang, Kaihao Zhang, Wenhan Luo +2
Blind Face Restoration (BFR) aims to construct a high-quality (HQ) face image from its corresponding low-quality (LQ) input. Recently, many BFR methods have been proposed and they…
Multi-Prior Learning via Neural Architecture Search for Blind Face Restoration
Yanjiang Yu, Puyang Zhang, Kaihao Zhang +4
Blind Face Restoration (BFR) aims to recover high-quality face images from low-quality ones and usually resorts to facial priors for improving restoration performance. However, cur…
FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks
Kaituo Feng, Changsheng Li, Ye Yuan +1
Knowledge distillation (KD) has demonstrated its effectiveness to boost the performance of graph neural networks (GNNs), where its goal is to distill knowledge from a deeper teache…
Scaling Up Maximal k-plex Enumeration
Qiangqiang Dai, Rong-Hua Li, Hongchao Qin +2
Finding all maximal -plexes on networks is a fundamental research problem in graph analysis due to many important applications, such as community detection, biological graph ana…
Self-Supervised Information Bottleneck for Deep Multi-View Subspace Clustering
Shiye Wang, Changsheng Li, Yanming Li +2
In this paper, we explore the problem of deep multi-view subspace clustering framework from an information-theoretic point of view. We extend the traditional information bottleneck…
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
Binhui Xie, Shuang Li, Mingjia Li +3
Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained on a labeled source do…