v222: Proceedings of ACML 2023

2026-06-10 · Source: Proceedings of Machine Learning Research · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Data Science & Analytics · Depth: Expert, long

Summary

Volume 222 presents the proceedings of the 15th Asian Conference on Machine Learning, held from November 11-14, 2023, in İstanbul, Turkey, edited by Berrin Yanıkoğlu and Wray Buntine. This extensive collection features a wide array of contributed papers spanning fundamental machine learning advancements and diverse applications. Key research areas include enhancing model interpretability and mitigating bias in image classification, novel approaches in Graph Neural Networks, and advancements in Reinforcement Learning for tasks like online bipartite matching and object navigation. The proceedings also cover innovations in Diffusion Models, Federated Learning, and Transformer architectures for various NLP and vision tasks. Furthermore, the volume explores techniques for robust and memory-efficient deep learning, alongside practical applications in medical imaging, recommendation systems, and urban prediction, offering significant insights into the current state and future directions of machine learning research across theoretical and practical domains.

Key takeaway

This volume compiles over 100 contributed papers from the 15th Asian Conference on Machine Learning (ACML 2023), showcasing advancements across diverse ML subfields. Key topics include mitigating bias in image classification, novel Graph Neural Network architectures, memory-efficient kernelized learning, diffusion models, and deep reinforcement learning applications. This collection offers researchers and practitioners cutting-edge insights and practical solutions for developing robust and efficient ML systems.

Topics

• Asian Conference on Machine Learning
• Graph Neural Networks
• Reinforcement Learning
• Diffusion Models
• Transformer Architectures

Best for: AI Scientist, Machine Learning Engineer, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Proceedings of Machine Learning Research.