AI 2024: Advances in Artificial Intelligence : 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25-29, 2024, Proceedings, Part II (Lecture Notes in Artificial Intelligence)

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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 II (Lecture Notes in Artificial Intelligence)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 445 p.
  • 言語 ENG
  • 商品コード 9789819603503

Full Description

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.

Contents

.- 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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