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Node Similarity Preserving Graph Convolutional Networks
WeiJin, TylerDerr, YiqiWang....
Published date-11/19/2020
GraphRepresentationLearning, RepresentationLearning, Self-SupervisedLearning
Graph Neural Networks (GNNs) have achieved tremendous success in various real-world applications due to their strong ability in graph representation learning. GNNs explore the graph structure and node features by …
Scalable Graph Neural Networks for Heterogeneous Graphs
LingfanYu, JiajunShen, JinyangLi....
Published date-11/19/2020
Graph neural networks (GNNs) are a popular class of parametric model for learning over graph-structured data. Recent work has argued that GNNs primarily use the graph for feature smoothing, and …
Creative Sketch Generation
SongweiGe, VedanujGoswami, C.LawrenceZitnick....
Published date-11/19/2020
Sketching or doodling is a popular creative activity that people engage in. However, most existing work in automatic sketch understanding or generation has focused on sketches that are quite mundane. …
FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
DiChai, LeyeWang, KaiChen....
Published date-11/19/2020
FederatedLearning
As an innovative solution for privacy-preserving machine learning (ML), federated learning (FL) is attracting much attention from research and industry areas. While new technologies proposed in the past few years …
Interpretable and Transferable Models to Understand the Impact of Lockdown Measures on Local Air Quality
JohannaEinsiedler, YunCheng, FranzPapst....
Published date-11/19/2020
TransferLearning
The COVID-19 related lockdown measures offer a unique opportunity to understand how changes in economic activity and traffic affect ambient air quality and how much pollution reduction potential can the …
Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks
RishabKhincha, UtkarshSarawgi, WazeerZulfikar....
Published date-11/19/2020
Clustering, Imputation
The problem of missing data has been persistent for a long time and poses a major obstacle in machine learning and statistical data analysis. Past works in this field have …