Online Asian Machine Learning School

The Online Asian Machine Learning School (OAMLS) aims to help prepare the next generation machine learning researchers and practitioners by providing them with knowledge of machine learning fundamentals as well as state-of-the-art advances. It focuses on participants in the Asia-Pacific region; the virtual format, supported by ever improving communication technologies, allows affordable participation from students and practitioners from a large part of the region, including those from under-represented areas, who may otherwise be unable to afford travel to a physical international school.

The School is part of the Asian Conference on Machine Learning. It will be held on November 8 - 19, 2021.

Why an online school? Physical schools have their advantages and our online school is not meant to replace them. However, international travel is required to attend the physical schools, limiting participation, particularly from those in regions not well represented in machine learning. Communication technologies have improved so much that we believe that an effective online school is possible. We aim to provide an interactive school, to build some of the bonds among participants that you would get in a physical school. To be able to do that effectively, we also expect strong commitment from the students participating in the school — to put aside time from their schedule to attend the school. We focus on the Asia-Pacific region to reduce the effect of time difference, minimising the need for night OAMLS (pronounced “owls” 😀) in different time-zones.

The application deadline has passed.

Schedule

Speakers

• 
  Angela Yao

  National University of Singapore
• 
  Cheng Soon Ong

  Data61, CSIRO
• 
  Cheng-Te Li

  National Cheng Kung University
• 
  Emtiyaz Khan

  RIKEN Center for Advanced Intelligence Project
• 
  Hung-yi Lee

  National Taiwan University
• 
  Jonas Peters

  University of Copenhagen
• 
  Nhat Ho

  University of Texas at Austin
• 
  Peter Bartlett

  University of California Berkeley
• 
  Reza Haffari

  Monash University
• 
  Sinno Pan

  Nanyang Technological University
• 
  Taiji Suzuki

  RIKEN Center for Advanced Intelligence Project/The University of Tokyo
• 
  Vered Shwartz

  University of British Columbia
• 
  Zhongwen Xu

  Sea AI Lab

Advisory Committee

• Hung Bui, VinAI Research
• Wray Buntine, Monash University
• Hsuan-Tien Lin, National Taiwan University
• Masashi Sugiyama, RIKEN Center for Advanced Intelligence Project/The University of Tokyo

Organizing Committee

• Titipat Achakulvisut, University of Pennsylvania
• Vivian Chen, National Taiwan University
• Wittawat Jitkrittum, Google Research
• Wee Sun Lee, National University of Singapore
• Nan Lu, University of Tokyo
• Ngan Vu, DeepMind
• Dani Yogatama, DeepMind

Sponsors

Platinum Sponsors

 

 

 

Gold Sponsors

 

Career Opportunities