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 and selected from 108 submissions. Part 1: Knowledge Representation and NLP; Trustworthy and Explainable AI; Machine Learning and Data Mining. Part 2: Reinforcement Learning and Robotics; Learning Algorithms; Computer Vision; AI for Healthcare.
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 and selected from 108 submissions.
Part 1: Knowledge Representation and NLP; Trustworthy and Explainable AI; Machine Learning and Data Mining. Part 2: Reinforcement Learning and Robotics; Learning Algorithms; Computer Vision; AI for Healthcare.
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Inhaltsangabe
.- Reinforcement Learning and Robotics. .- ECoDe: A Sample-Efficient Method for Co-Design of Robotic Agents. .- Causally driven hierarchies for Feudal Multi-Agent Reinforcement Learning. .- Graceful Task Adaptation with a Bi-Hemispheric RL Agent. .- Towards Virtual Character Control via Partial Story Sifting. .- Boosting Reinforcement Learning Algorithms in Continuous Robotic Reaching Tasks using Adaptive Potential Functions. .- Online Deep Reinforcement Learning of Servo Control for a Small-Scale Bio-Inspired Wing. .- Posterior Tracking Algorithm for Multi-objective Classification Bandits. .- Learning Algorithms .- Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation. .- Pathwise Gradient Variance Reduction with Control Variates in Variational Inference. .- Active Continual Learning: On Balancing Knowledge Retention and Learnability. .- Bayesian Parametric Proportional Hazards Regression with the Fused Lasso. .- Revisiting Bagging for Stochastic Algorithms. .- Sampling of Large Probabilistic Graphical Models Using Arithmetic Circuits. .- Importance-based Pruning for Genetic Programming based Symbolic Regression. .- Quantifying Manifolds: Do the Manifolds Learned by Generative Adversarial Networks Converge to the Real Data Manifold?. .- Equality Generating Dependencies in Description Logics via Path Agreements. .- Computer Vision .- End-to-end Truck Speed Detection using Deep Multi-Task Learning. .- Real-Time Lightweight 3D Hand-Object Pose Estimation Using Temporal Graph Convolution Networks. .- New Perspectives for the Deep Learning Based Photography Aesthetics Assessment. .- 3DSSG-Cap: A Caption Enhanced Dataset for 3D Visual Grounding. .- Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. .- Chain of Thought Prompting in Vision-Language Model for Vision Reasoning Tasks. .- Enabling Visual Intelligence by Leveraging Visual Object States in a Neurosymbolic Framework. .- AI for Healthcare .- A Self-Adaptive Framework for Efficient Cell Detection and Segmentation in Histopathological Images with Minimal Expert Input. .- Learning Low-Energy Consumption Obstacle Detection Models for the Blind. .- Claimsformer: Pretrained Transformer for Administrative Claims Data to Predict Chronic Conditions. .- Online Machine Learning for Real-Time Cell Culture Process Monitoring. .- Motif-induced Subgraph Generative Learning for Explainable Neurological Disorder Detection. .- Multimodal Hyperbolic Graph Learning for Alzheimer's Disease Detection. .- Real-Time Human Activity Recognition Using Non-Intrusive Sensing and Continual Learning. .- Unsupervised dMRI Artifact Detection via Angular Resolution Enhancement and Cycle Consistency Learning. .- Assessment of Left Atrium Motion Deformation Through Full Cardiac Cycle. .- Vision-Based Abnormal Action Dataset for Recognising Body Motion Disorders.
.- Reinforcement Learning and Robotics. .- ECoDe: A Sample-Efficient Method for Co-Design of Robotic Agents. .- Causally driven hierarchies for Feudal Multi-Agent Reinforcement Learning. .- Graceful Task Adaptation with a Bi-Hemispheric RL Agent. .- Towards Virtual Character Control via Partial Story Sifting. .- Boosting Reinforcement Learning Algorithms in Continuous Robotic Reaching Tasks using Adaptive Potential Functions. .- Online Deep Reinforcement Learning of Servo Control for a Small-Scale Bio-Inspired Wing. .- Posterior Tracking Algorithm for Multi-objective Classification Bandits. .- Learning Algorithms .- Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation. .- Pathwise Gradient Variance Reduction with Control Variates in Variational Inference. .- Active Continual Learning: On Balancing Knowledge Retention and Learnability. .- Bayesian Parametric Proportional Hazards Regression with the Fused Lasso. .- Revisiting Bagging for Stochastic Algorithms. .- Sampling of Large Probabilistic Graphical Models Using Arithmetic Circuits. .- Importance-based Pruning for Genetic Programming based Symbolic Regression. .- Quantifying Manifolds: Do the Manifolds Learned by Generative Adversarial Networks Converge to the Real Data Manifold?. .- Equality Generating Dependencies in Description Logics via Path Agreements. .- Computer Vision .- End-to-end Truck Speed Detection using Deep Multi-Task Learning. .- Real-Time Lightweight 3D Hand-Object Pose Estimation Using Temporal Graph Convolution Networks. .- New Perspectives for the Deep Learning Based Photography Aesthetics Assessment. .- 3DSSG-Cap: A Caption Enhanced Dataset for 3D Visual Grounding. .- Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. .- Chain of Thought Prompting in Vision-Language Model for Vision Reasoning Tasks. .- Enabling Visual Intelligence by Leveraging Visual Object States in a Neurosymbolic Framework. .- AI for Healthcare .- A Self-Adaptive Framework for Efficient Cell Detection and Segmentation in Histopathological Images with Minimal Expert Input. .- Learning Low-Energy Consumption Obstacle Detection Models for the Blind. .- Claimsformer: Pretrained Transformer for Administrative Claims Data to Predict Chronic Conditions. .- Online Machine Learning for Real-Time Cell Culture Process Monitoring. .- Motif-induced Subgraph Generative Learning for Explainable Neurological Disorder Detection. .- Multimodal Hyperbolic Graph Learning for Alzheimer's Disease Detection. .- Real-Time Human Activity Recognition Using Non-Intrusive Sensing and Continual Learning. .- Unsupervised dMRI Artifact Detection via Angular Resolution Enhancement and Cycle Consistency Learning. .- Assessment of Left Atrium Motion Deformation Through Full Cardiac Cycle. .- Vision-Based Abnormal Action Dataset for Recognising Body Motion Disorders.
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