Data Science and Machine Learning

23rd Australasian Conference, AusDM 2025, Brisbane, QLD, Australia, November 26–28, 2025, Proceedings

AvQuang Vinh Nguyen,Yuefeng Li

Häftad, Engelska, 2026

Del i serien Communications in Computer and Information Science

858 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2026-02-13
Mått:155 x 235 x 32 mm
Vikt:867 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:562
Förlag:Springer Verlag, Singapore
ISBN:9789819567850

Utforska kategorier

Databaser inom Data och IT
Systemvetenskap och AI inom Data och IT

Innehållsförteckning

.- 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 SafetyInsights..- 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.