EVENT: The International Conference on Learning Representations 2020 (ICLR 2020)
THEME: Artificial Intelligence (AI) for Affordable Healthcare
DATE: April 26–30, 2020
VENUE: Millennium Hall, Addis Ababa, Ethiopia
(ICLR) – Healthcare is under significant pressure: costs are rising, populations are aging, lifestyles are becoming more sedentary, and critically we lack experts to meet the rising demand. In addition, in under-developed countries healthcare quality remains limited. Meanwhile, AI has shown great promise for healthcare applications, and the digitization of data and use of electronic health records is becoming more widespread. AI could play a key role in enabling, democratizing and upholding high standards of healthcare worldwide, assisting health professionals to make decisions faster, more accurately and more consistently.
However, so far, the adoption of AI in real-world healthcare applications has been slow relative to that in domains such as autonomous driving. In this workshop, we aim to highlight recent advances and the potential opportunities, via a series of talks and panel discussion. We invite papers addressing general challenges important to the real-world deployment of AI in healthcare.
About International Conference on Learning Representations (ICLR)
The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.
Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
A non-exhaustive list of relevant topics explored at the conference include:
- unsupervised, semi-supervised, and supervised representation learning,
- representation learning for planning and reinforcement learning
- metric learning and kernel learning,
- sparse coding and dimensionality expansion,
- hierarchical models,
- optimization for representation learning,
- learning representations of outputs or states,
- implementation issues, parallelization, software platforms, hardware,
- applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field.
Dates | Speakers | Call for papers | Schedule | Organizers
Source: ICLR