10.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of SydneyAU198 papers
- Centre for Quantum Computation and Communication TechnologyAU120 papers
- UNSW SydneyAU97 papers
- Australian National UniversityAU88 papers
- Tsinghua UniversityCN80 papers
- Commonwealth Scientific and Industrial Research OrganisationAU75 papers
- Chinese Academy of SciencesCN74 papers
- Macquarie UniversityAU68 papers
- The University of MelbourneAU50 papers
- Data61AU43 papers
- ARC Centre of Excellence for Transformative Meta-Optical SystemsAU41 papers
- Nanyang Technological UniversitySG41 papers
7 papers · 2 filters
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
Sheng Xiang, Mingzhi Zhu, Dawei Cheng +5
Credit card fraud incurs a considerable cost for both cardholders and issuing banks. Contemporary methods apply machine learning-based classifiers to detect fraudulent behavior fro…
Enhancing Imbalance Learning: A Novel Slack-Factor Fuzzy SVM Approach
M. Tanveer, Anushka Tiwari, Mushir Akhtar +1
In real-world applications, class-imbalanced datasets pose significant challenges for machine learning algorithms, such as support vector machines (SVMs), particularly in effective…
Effective Predictive Modeling for Emergency Department Visits and Evaluating Exogenous Variables Impact: Using Explainable Meta-learning Gradient Boosting
Mehdi Neshat, Michael Phipps, Nikhil Jha +3
Over an extensive duration, administrators and clinicians have endeavoured to predict Emergency Department (ED) visits with precision, aiming to optimise resource distribution. Des…
A Data-Driven Review of Remote Sensing-Based Data Fusion in Precision Agriculture from Foundational to Transformer-Based Techniques
Mahdi Saki, Rasool Keshavarz, Daniel Franklin +3
This review explores recent advancements in data fusion techniques and Transformer-based remote sensing applications in precision agriculture. Using a systematic, data-driven appro…
RIDA: A Robust Attack Framework on Incomplete Graphs
Jianke Yu, Hanchen Wang, Chen Chen +5
Graph Neural Networks (GNNs) are vital in data science but are increasingly susceptible to adversarial attacks. To help researchers develop more robust GNN models, it's essential t…
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification
Hui Chen, Hengyu Liu, Zhangkai Wu +2
While deep neural networks (DNNs) based personalized federated learning (PFL) is demanding for addressing data heterogeneity and shows promising performance, existing methods for f…
MatchNAS: Optimizing Edge AI in Sparse-Label Data Contexts via Automating Deep Neural Network Porting for Mobile Deployment
Hongtao Huang, Xiaojun Chang, Wen Hu +1
Recent years have seen the explosion of edge intelligence with powerful Deep Neural Networks (DNNs). One popular scheme is training DNNs on powerful cloud servers and subsequently…