Overview

This book constitutes the proceedings of the 23rd Australasian Conference on Data Science and Machine Learning, AusDM 2025, held in Brisbane, Australia, during November 26-28, 2025. The 37 full papers presented in this book were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: (1) Federated, Adaptive and Trustworthy Machine Learning; (2) Environment, Information Security and Productivity; (3) Deep Learning Fusion and Vision; (4) Health and Social Good and (5) Knowledge-Driven and Domain Specific AI. They deal with topics around data science, machine learning and also AI in everyday life.

Full Product Details

Author:   Quang Vinh Nguyen ,  Yuefeng Li ,  Paul Kwan ,  Yanchang Zhao
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
ISBN:  

9789819567850

ISBN 10:   9819567858
Pages:   562
Publication Date:   13 February 2026
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

.- Federated, Adaptive, and Trustworthy Machine Learning. .- DAARA: Divergence-Aware Attention for Robust Aggregation in Federated Learning Against Poisoning Attacks. .- Understanding the Asymmetric Impact of Forecast Accuracy on Decision Quality. .- WaveFSL: Wave Interference-Based Meta-Learning for Few-Shot Cross-Modality Traffic Forecasting. .- FedMOAR: Multi-Objective Adaptive Regularization for Fair and Efficient Federated Learning. .- Unveiling Reliability in Multi-Omics Classification:Fusion, Calibration, and Dynamic Scaling. .- Stability Evaluation of Clusterings Across Time. .- DriftSense: Adaptive Drift Detection with Incremental Hoeffding Trees for Real-Time Spatial Crowdsourcing. .- Dynamic Meta-Learning Ensemble for Financial Forecasting. .- Environment, Information Security and Productivity. .- Effective Missing-Data Imputation for Time Series with Seasonality and Causality. .- UniCausal: A Unified Approach to Causal Discovery from Hybrid Industrial Time Series and Events. .- Dynamic Source Code Vulnerability Characteristics Selection for Enhanced Vulnerability Discover. .- Modelling Financial Time Series of Returns and Covariance Matrices Using Time-Space Transformers. .- Temporal Fusion of Biophysical and Climate Data: A Data-Driven Hybrid Learning Approach for Short-Term Aboveground Biomass Forecasting. .- Precision to Costing: Budgeted Modelling for Customer Contact Prediction. .- Defining Responsible AI: Contextual Insights Powered by LLMs. .- Deep Learning Fusion and Vision. .- Fusing Deep Object Detectors via Spatial Heatmap-Based Relevance Modeling. .- CarDamageEval: Benchmark Evaluation of Car Damage Assessment Using Vision Language Models. .- Regularizing StyleGAN with Inter-Resolution Residual Pattern Consistency via a Laplacian Pyramid. .- Mixup and Local-FOMA based Two-Phase Manifold Augmentation in Image Classification. .- BARE: Boundary-Aware with Resolution Enhancement for Tree Crown Delineation. .- Integrating Vision Transformers and Autoencoders for Interpretable Cancer Risk Assessment. .- LightSkinNet: Lightweight CNN with Attention for Accurate,Mobile-Efficient Multiclass Skin Lesion Classification. .- A DenseNet-YOLOv8 Fusion Model for Intelligent Parasite Egg Detection and Classification. .- Health and Social Good. .- An AI-Driven Framework for Real-Time Reporting and Identification of Lost Cats. .- Benchmarking Preprocessing and Integration Methods in Single-Cell Genomics. .- Towards Automated Differential Diagnosis of Skin Diseases Using Deep Learning and Imbalance-Aware Strategies. .- Causal Recommendation Method for Personalised Chemotherapy Optimisation in Breast Cancer. .- Machine Learning for Traffic Accident Prediction: Integrating Spatial and Behavioral Data for Road Safety Insights. .- Visionary: Enhancing Visual Context for the Visually Impaired. .- Knowledge-Driven and Domain Specific AI. .- Advancing Atayal Language Preservation with AI-Driven Multimodal Speech and Text Processing. .- ETCOD: Embedding-Based Anomaly Detection and LLM-Driven Validation Framework for Knowledge Graphs. .- Top-k Ranking with Exact Positional Fairness. .- Evaluating Structural Preprocessing in RAG for Academic Curriculum Applications. .- Evaluating Cross-Lingual Classification Strategies EnablingTopic Discovery for Multilingual Social Media Data. .- From Burst to Routine: Mining Time-Compact Patterns from Sequential Dataset. .- A Parameter-free Method Tuning for Multi-scale Wildfire Images Retrieval Task. .- NeuroPhysNet: A FitzHugh-Nagumo-Based Physics-InformedNeural Network Framework for Electroencephalograph (EEG)Analysis and Motor Imagery Classification.

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