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ICMLC 2027: International Conference on Machine Learning and Computing

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ICMLC
截稿日期:
2026-09-25 还有 80 天
通知日期:
2026-10-25
会议日期:
2027-02-26
会议地点:
Shenzhen, China
届数:
QUALIS: B4   浏览: 51979   关注: 69   参加: 27

征稿

ICMLC 2027 (International Conference on Machine Learning and Computing) is a QUALIS B4 conference held in Shenzhen, China on 2027-02-26. The paper submission deadline is 2026-09-25. Acceptance notifications are sent on 2026-10-25.

The 19th International Conference on Machine Learning and Computing is the premier forum for new ideas and experimental results in machine learning and computing. The conference specifically seeks particularly forward-looking and novel submissions. Papers are solicited on a broad range of topics, including (but not limited to): Track 1: Theoretical Foundations of Machine Learning Computational Learning Theory Statistical Learning Theory PAC Learning VC Dimension Track 2: Supervised Learning Linear Regression Logistic Regression Decision Trees Support Vector Machines Track 3: Unsupervised Learning Clustering Analysis Association Rule Mining Principal Component Analysis Track 4: Reinforcement Learning Q-Learning Policy Gradient Methods Applications in Robotics and Game AI Track 5: Deep Learning Convolutional Neural Networks Recurrent Neural Networks Transformer Architecture Track 6: Applications of Machine Learning Computer Vision Natural Language Processing Bioinformatics Business Intelligence and Data Analytics Track 7: Data Management and Processing Big Data Processing Data Mining and Knowledge Discovery Data Cleaning and Integration Track 8: Natural Language Processing (NLP) Large Language Models (LLMs) Multimodal NLP (Text+Vision/Audio) Low-Resource/Domain-Specific NLP Track 9: Human-Computer Interaction in Machine Learning User-Friendly Machine Learning Interfaces Human-Machine Collaboration Visualization of Machine Learning Processes
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相关期刊

CCF全称影响因子出版商ISSN
BMachine Learning2.9Springer0885-6125
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CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
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