541 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nanyang Technological UniversitySG56 papers
- National University of SingaporeSG46 papers
- Zhejiang UniversityCN43 papers
- Monash UniversityAU29 papers
- Singapore University of Technology and DesignSG21 papers
- Chinese University of Hong KongHK19 papers
- Hong Kong University of Science and TechnologyHK18 papers
- Institute for Infocomm ResearchSG18 papers
- Humboldt-Universität zu BerlinDE15 papers
- Agency for Science, Technology and ResearchSG13 papers
- Alibaba Group (China)CN13 papers
- Carnegie Mellon UniversityUS13 papers
7 papers · 2 filters
Building Legal Datasets
Jerrold Soh
Data-centric AI calls for better, not just bigger, datasets. As data protection laws with extra-territorial reach proliferate worldwide, ensuring datasets are legal is an increasin…
Node-wise Localization of Graph Neural Networks
Zemin Liu, Yuan Fang, Chenghao Liu +1
Graph neural networks (GNNs) emerge as a powerful family of representation learning models on graphs. To derive node representations, they utilize a global model that recursively a…
Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling
Peixin Zhang, Jingyi Wang, Jun Sun +5
Although deep learning has demonstrated astonishing performance in many applications, there are still concerns about its dependability. One desirable property of deep learning appl…
Probabilistic Verification of Neural Networks Against Group Fairness
Bing Sun, Jun Sun, Ting Dai +1
Fairness is crucial for neural networks which are used in applications with important societal implication. Recently, there have been multiple attempts on improving fairness of neu…
: Compositional Counterfactual Contrastive Learning for Video-grounded Dialogues
Hung Le, Nancy F. Chen, Steven C. H. Hoi
Video-grounded dialogue systems aim to integrate video understanding and dialogue understanding to generate responses that are relevant to both the dialogue and video context. Most…
FL-Market: Trading Private Models in Federated Learning
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa +2
The difficulty in acquiring a sufficient amount of training data is a major bottleneck for machine learning (ML) based data analytics. Recently, commoditizing ML models has been pr…
Meta-Inductive Node Classification across Graphs
Zhihao Wen, Yuan Fang, Zemin Liu
Semi-supervised node classification on graphs is an important research problem, with many real-world applications in information retrieval such as content classification on a socia…