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活动简介

Welcome to the 9th Asian Conference on Machine Learning (ACML 2017). The conference will take place on November 15 - 17, 2017 at Baekyang Hall of Yonsei University campus, Seoul, Korea. We invite professionals and researchers to discuss research results and ideas in machine learning. We seek original and novel research papers resulting from theory and experiment of machine learning. The conference also solicits proposals focusing on disruptive ideas and paradigms within the scope. We encourage submissions from all parts of the world, not only confined to the Asia-Pacific region.

As machine plays critical role in various fields of industry, machine learning researchers needed to gather and share new ideas and achievements at a forum. ACML has begun to take place annually over the Asian regions since 2009. This is the 9th Conference to be held in Seoul, Korea after 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). The conference has contributed to understanding the machine leaning, bringing inspiration to scientists, and applying the technologies to industries. This conference will consist of informative and integrated programs as traditions of the previous ones.

Yonsei University, one of most prestigious universities, is about 130 years old historical campus in Korea. The University street called "Sinchon" is connected to Ewha Womans University and Hongik University as one of youth hotspots. You can walk along ‘Sinchon’s Pedestrian Friendly Street’ which is full of cafes, fashion items, and beauty goods. The district is located at the heart of Seoul with easy access to cultural and attractive sites. Seoul is ranked by Asian tourists as their favorite world city three years in a row. Come experience the history and excitement of modern Seoul.

征稿信息

重要日期

2017-05-10
初稿截稿日期
2017-06-20
初稿录用日期
2017-08-05
终稿截稿日期

征稿范围

  • Learning problems

  • Active learning

  • Bayesian machine learning

  • Deep learning, latent variable models

  • Dimensionality reduction

  • Feature selection

  • Graphical models

  • Learning for big data

  • Learning in graphs

  • Multiple instance learning

  • Multi-objective learning

  • Multi-task learning

  • Semi-supervised learning

  • Sparse learning

  • Structured output learning

  • Supervised learning

  • Online learning

  • Transfer learning

  • Unsupervised learning

  • Analysis of learning systems

  • Computational learning theory

  • Experimental evaluation

  • Knowledge refinement

  • Reproducible research

  • Statistical learning theory

  • Applications

  • Bioinformatics

  • Biomedical information

  • Collaborative filtering

  • Healthcare

  • Computer vision

  • Human activity recognition

  • Information retrieval

  • Natural language processing

  • Social networks

  • Web search

  • Learning in knowledge-intensive systems

  • Knowledge refinement and theory revision

  • Multi-strategy learning

  • Other systems

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重要日期
  • 会议日期

    11月15日

    2017

    11月17日

    2017

  • 05月10日 2017

    初稿截稿日期

  • 06月20日 2017

    初稿录用通知日期

  • 08月05日 2017

    终稿截稿日期

  • 11月17日 2017

    注册截止日期

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