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ORCID21st AusDM 2023: Auckland, New Zealand
- Diana Benavides-Prado
, Sarah M. Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh:
Data Science and Machine Learning - 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023, Proceedings. Communications in Computer and Information Science 1943, Springer 2024, ISBN 978-981-99-8695-8
Research Track
- Nan Yang, Laicheng Zhong, Fan Huang, Wei Bao, Dong Yuan:
Random Padding Data Augmentation. 3-18 - Shaowen Tang, Raymond Wong:
Unsupervised Fraud Detection on Sparse Rating Networks. 19-33 - Ying Cui, Louise McMillan, Ivy Liu:
Semi-supervised Model-Based Clustering for Ordinal Data. 34-47 - Ali Anaissi, Yuanzhe Jia, Ali Braytee, Mohamad Naji, Widad Alyassine:
Damage GAN: A Generative Model for Imbalanced Data. 48-61 - Michael Longland, David Liebowitz, Kristen Moore, Salil S. Kanhere:
Text-Conditioned Graph Generation Using Discrete Graph Variational Autoencoders. 62-74 - Liang Tang, Qianqian Qi, Qinghua Shang, Yuguang Cai, Jiamou Liu, Michael Witbrock, Kaokao Lv:
Boosting QA Performance Through SA-Net and AA-Net with the Read+Verify Framework. 75-89 - Sadeq Darrab, Harshitha Allipilli, Sana Ghani, Harikrishnan Changaramkulath, Sricharan Koneru, David Broneske, Gunter Saake:
Anomaly Detection Algorithms: Comparative Analysis and Explainability Perspectives. 90-104 - Manh Khoi Duong, Stefan Conrad:
Towards Fairness and Privacy: A Novel Data Pre-processing Optimization Framework for Non-binary Protected Attributes. 105-120 - Kamaladdin Fataliyev, Wei Liu:
MStoCast: Multimodal Deep Network for Stock Market Forecast. 121-136 - Sayed Waleed Qayyumi, Laurence A. F. Park, Oliver Obst:
Few-Shot and Transfer Learning with Manifold Distributed Datasets. 137-149 - Din Muhammad Sangrasi, Lei Wang, Markus Hagenbuchner, Peng Wang:
Mitigating the Adverse Effects of Long-Tailed Data on Deep Learning Models. 150-162 - Chunyu Wang, Qi Chen, Bing Xue, Mengjie Zhang:
Shapley Value Based Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression. 163-176 - Tulika Shrivastava, Basem Suleiman, Muhammad Johan Alibasa:
Hybrid Models for Predicting Cryptocurrency Price Using Financial and Non-Financial Indicators. 177-191
Application Track
- Amit Vurgaft:
Multi-dimensional Data Visualization for Analyzing Materials. 195-210 - Tobias Milz, Elizabeth Macpherson, Varvara Vetrova:
Law in Order: An Open Legal Citation Network for New Zealand. 211-225 - Li Xiao, Samaneh Madanian, Weihua Li, Yuchun Xiao:
Enhancing Resource Allocation in IT Projects: The Potentials of Deep Learning-Based Recommendation Systems and Data-Driven Approaches. 226-238 - Fathima Nuzla Ismail, Abira Sengupta, Brendon J. Woodford, Sherlock A. Licorish:
A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California. 239-253 - Qurrat Ul Ain, Bing Xue, Harith Al-Sahaf, Mengjie Zhang:
Skin Cancer Detection with Multimodal Data: A Feature Selection Approach Using Genetic Programming. 254-269 - Prathayne Nanthakumaran, Liwan Liyanage:
Comparison of Interpolation Techniques for Prolonged Exposure Estimation: A Case Study on Seven Years of Daily Nitrogen Oxide in Greater Sydney. 270-283 - Sedigh Khademi, Christopher Palmer, Muhammad Javed, Gerardo Luis Dimaguila, Jim P. Buttery, Jim Black:
Detecting Asthma Presentations from Emergency Department Notes: An Active Learning Approach. 284-298
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