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05/17/2023
Characterizing Long-Tail Categories on Graphs
Long-tail data distributions are prevalent in many real-world networks, ...
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09/27/2022
Retrieval Based Time Series Forecasting
Time series data appears in a variety of applications such as smart tran...
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08/15/2022
ARIEL: Adversarial Graph Contrastive Learning
Contrastive learning is an effective unsupervised method in graph repres...
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05/31/2022
COIN: Co-Cluster Infomax for Bipartite Graphs
Bipartite graphs are powerful data structures to model interactions betw...
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02/14/2022
Adversarial Graph Contrastive Learning with Information Regularization
Contrastive learning is an effective unsupervised method in graph repres...
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10/28/2021
Graph Communal Contrastive Learning
Graph representation learning is crucial for many real-world application...
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09/08/2021
Graph-MVP: Multi-View Prototypical Contrastive Learning for Multiplex Graphs
Contrastive Learning (CL) is one of the most popular self-supervised lea...
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08/29/2021
Multiplex Graph Neural Network for Extractive Text Summarization
Extractive text summarization aims at extracting the most representative...
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02/15/2021
HDMI: High-order Deep Multiplex Infomax
Networks have been widely used to represent the relations between object...
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02/15/2021
Network of Tensor Time Series
Co-evolving time series appears in a multitude of applications such as e...
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05/22/2020
SODA: Detecting Covid-19 in Chest X-rays with Semi-supervised Open Set Domain Adaptation
The global pandemic of COVID-19 has infected millions of people since it...
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04/26/2020
Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports
Chest X-Ray (CXR) images are commonly used for clinical screening and di...
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05/28/2019
Adversarial Domain Adaptation Being Aware of Class Relationships
Adversarial training is a useful approach to promote the learning of tra...
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09/16/2018
Cross-Domain Labeled LDA for Cross-Domain Text Classification
Cross-domain text classification aims at building a classifier for a tar...
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11/22/2017
