OAMLS: Online Asian Machine Learning School
The Online Asian Machine Learning School (OAMLS), an initiative and part of the Asian Conference on Machine Learning (ACML), aims to help prepare the next generation of machine learning researchers and practitioners by providing them with knowledge of machine learning fundamentals as well as state-of-the-art advancements in the field. Leading international researchers in machine learning will be invited to provide lectures and tutorials on these topics, which will prepare students for research and innovation in machine learning.
This school focuses on participants in the Asia-Pacific region. The school will be held in the virtual format, supported by ever-improving communication technologies, to allow affordable participation from students and practitioners from the region, including those from under-represented areas, who may otherwise be unable to afford travel to a physical international school. The target audience for OAMLS is early-stage graduate students or practitioners in tech companies (or entrepreneurs) with backgrounds similar to early-stage graduate students. We expect the participants to eventually become influential researchers in the region. The applicants will be screened by an expert selection panel to select strongly motivated and talented participants from the region. We hope the school participants will also attend the ACML conference, and interact with conference participants to see and learn from new ideas, progress and achievements in the field.
Topics covered at OAMLS last year include Machine learning for computer vision, computational biology, machine learning from Bayesian perspective, Generalization theory, Causality, Theory and optimization, Graph representation, Natural language processing, Reinforcement learning, and more. We believe that participants will gain knowledge from variety of researchers and practitioners in the fields as well as discuss their research.
Call for ApplicationsFor call for applications for OAMLS, please refer here.
DatesOAMLS would be conducted on the following dates: Dec 8-10 and Dec 15-16.
More details would be updated here.
- Kun Zhang , Carnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
- Leslie Kaelbling , Massachusetts Institute of Technology
- Arthur Gretton , University College London
- Petar Veličković , Deep Mind
- Mijung Park, University of British Columbia
- Masaaki Imaizumi, The University of Tokyo
- C V Jawahar, International Institute of Information Technology, Hyderabad
- Chiranjib Bhattacharyya, India Institute of Science, Bangalore
- Swabha Swayamdipta, USC Viterbi School of Engineering
- Pin-Yu Chen, IBM Research
- Hung Bui, VinAI Research
- Wray Buntine, VinUniversity, Vietnam
- Hsuan-Tien Lin, National Taiwan University
- Masashi Sugiyama, RIKEN Center for Advanced Intelligence Project/The University of Tokyo
- Titipat Achakulvisut, Mahidol University
- Barış Akgün, Koç University
- Vivian Chen, National Taiwan University
- Bo Han, Hong Kong Baptist University
- Wittawat Jitkrittum, Google Research
- Wee Sun Lee, National University of Singapore
- Nan Lu, University of Tokyo
- P.K. Srijith, Indian Institute of Technology Hyderabad
- Dani Yogatama, DeepMind
- Ngân (NV) Vũ, DeepMind