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AI 2024: Advances in Artificial Intelligence 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25–29, 2024, Proceedings, Part I /

This two-volume set LNAI 15442-15443 constitutes the refereed proceedings of the 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, held in Melbourne, VIC, Australia, during November 25-29, 2024. The 59 full papers presented together with 3 short papers were carefully reviewed a...

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Korporativní autor: SpringerLink (Online service)
Další autoři: Gong, Mingming (Editor), Song, Yiliao (Editor), Koh, Yun Sing (Editor), Xiang, Wei (Editor), Wang, Derui (Editor)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Vydání:1st ed. 2025.
Edice:Lecture Notes in Artificial Intelligence, 15442
Témata:
Artificial intelligence.
Computer networks .
Data mining.
Application software.
Computer vision.
Artificial Intelligence.
Computer Communication Networks.
Data Mining and Knowledge Discovery.
Computer and Information Systems Applications.
Computer Vision.
On-line přístup:https://doi.org/10.1007/978-981-96-0348-0
Tagy: Přidat tag
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Obsah:
  • -- Knowledge Representation and NLP.
  • DELA: Dual Embedding Using LSTM and Attention for Asset Tag Inference in Industrial Automation Systems.
  • Combined Change Operators for Trust and Belief.
  • Highlighting Case Studies in LLM Literature Review of Interdisciplinary System Science.
  • Legal Judgment Prediction through Argument Analysis.
  • Conditional Prototypical Optimal Transport for Enhanced Clue Identification in Multiple Choice Question Answering.
  • REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models.
  • Leveraging LLM in Genetic Programming Hyper-Heuristics for Dynamic Microservice Deployment.
  • Bidirectional Dependency Representation Disentanglement for Time Series Classification.
  • SCODA - A Framework for Software Capability Representation and Inspection.
  • Some Considerations for the Preservation of Endangered Languages Using Low-Resource Machine Translation.
  • Trustworthy and Explainable AI.
  • Improving Intersectional Group Fairness Using Conditional Generative Adversarial Network and Transfer Learning.
  • GPT-4 Attempting to Attack AI-Text Detectors.
  • Charting a Fair Path: FaGGM Fairness-aware Generative Graphical Models.
  • Shedding Light on Greenwashing: Explainable Machine Learning for Green Ad Detection.
  • Beyond Factualism: A Study of LLM Calibration through the Lens of Conversational Emotion Recognition.
  • Ensuring Fairness in Stochastic Multi-Armed Bandit Problems for Effective Group Recommendations.
  • Human Decision-Making Concepts with Goal-Oriented Reasoning for Explainable Deep Reinforcement Learning.
  • Towards Explainable Deep Learning for Non-melanoma Skin Cancer Diagnosis.
  • Machine Learning and Data Mining.
  • Localization System Enhanced with CDLPE: A Low-Cost, Resilient Map-Matching Algorithm.
  • FocDepthFormer: Transformer with latent LSTM for Depth Estimation from Focal Stack.
  • TSI: A Multi-View Representation Learning Approach for Time Series Forecasting.
  • Climate Downscaling Monthly Coastal Sea Surface Temperature Using Convolutional Neural Network and Composite Loss.
  • DBSSM: Deep BERT-based Semantic Skill Matching from Resumes to a Public Skill Taxonomy.
  • Designing an Adaptive AI System for Operation on Board the SpIRIT Nano-satellite.
  • LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction.
  • An Improved Prescriptive Tree-based Model for Stochastic Parallel Machine Scheduling.
  • Economic Graph Lottery Ticket: A GNN based Economic Forecasting Model.
  • Pattern-based Trading by Continual Learning of Price and Volume Patterns.
  • An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting.

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