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All CFPs on WikiCFP | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Present CFP : 2025 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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The 17th Asian Conference on Machine Learning (ACML 2025) will take place between December 9th - 12th, 2025, in Taipei, Taiwan. The conference aims to provide a leading international forum for researchers in machine learning and related fields to share their new ideas, progress, and achievements.
The conference calls for high-quality, original research papers in the theory and practice of machine learning. The conference also solicits proposals focusing on frontier research, new ideas, and paradigms in machine learning. We encourage submissions from all parts of the world, not only confined to the Asia-Pacific region. Topics of interest include but are not limited to: General machine learning Active learning Bayesian machine learning Clustering Imitation Learning Learning to Rank Meta-Learning Multi-objective learning Multiple instance learning Multi-task learning Neuro-symbolic methods Online learning Optimization Reinforcement learning Relational learning Self-supervised learning Semi-supervised learning Structured output learning Supervised learning Transfer learning Unsupervised learning Weakly-supervised learning Learning with noisy labels Other machine learning methodologies Deep learning Architectures Deep reinforcement learning Generative models Multi-modality learning Large-language models and other foundation models Deep learning theory Other topics in deep learning Theory Bandits Computational learning theory Game theory Optimization Statistical learning theory Other theories Datasets and reproducibility Implementations, libraries ML datasets and benchmarks Other topics in reproducible ML research Trustworthy machine learning Accountability, explainability, transparency Adversarial learning Causality Fairness Privacy Robustness AutoML Other topics in trustworthy ML Learning in knowledge-intensive systems Knowledge refinement and theory revision Multi-strategy learning Other systems Applications Bioinformatics Biomedical informatics Climate science Collaborative filtering Computer vision Healthcare Human activity recognition Information retrieval Natural language processing Social good Social networks Web search ML for science Other applications | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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