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All CFPs on WikiCFP | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Present CFP : 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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The 16th Asian Conference on Machine Learning (ACML 2024) will take place in Hanoi, Vietnam. 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. Submissions from regions other than the Asia-Pacific are also highly encouraged.
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. ACML has taken place annually since 2009 in locations throughout the Asia-Pacific region. This is the 2024 Conference to be held in Hanoi, Vietnam after previous conferences were held in İstanbul, Turkey (2023), Hyderabad, India (2022), virtual mode (2021), Bangkok (converted to virtual mode), Thailand (2020), Nagoya, Japan (2019), Beijing, China (2018), Seoul, Korea (2017), Hamilton, New Zealand (2016), Hong Kong, China (2015), Nha Trang, Vietnam (2014), Canberra, Australia (2013), Singapore (2012), Taoyuan, Taiwan (2011), Tokyo, Japan (2010), and Nanjing, China (2009). Topics of interest include but are not limited to: General machine learning Active learning Bayesian machine learning Dimensionality reduction Feature selection Graphical models Imitation Learning Latent variable models Learning for big data Learning from noisy supervision Learning in graphs Multi-objective learning Multiple instance learning Multi-task learning Online learning Optimization Reinforcement learning Relational learning Semi-supervised learning Sparse learning Structured output learning Supervised learning Transfer learning Unsupervised learning Other machine learning methodologies Deep learning Attention mechanism and transformers Deep learning theory Generative models Deep reinforcement learning Architectures Other topics in deep learning Theory Computational learning theory Optimization (convex, non-convex) Reproducible research Bandits Statistical learning theory Other theories Trustworthy Machine Learning Accountability/Explainability/Transparency Causality Fairness Privacy Robustness Other topics in trustworthy ML Applications Bioinformatics Biomedical informatics Collaborative filtering Computer vision COVID-19 related research Healthcare Human activity recognition Information retrieval Natural language processing Social networks Web search Climate science Other applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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