[ML-news] Call for Papers: PML4DC Workshop @ ICLR 2022
Meareg A. Hailemariam
Apologies for cross-posting.
We are happy to invite you to contribute towards the 3rd Practical ML for Developing Countries (PML4DC) workshop at ICLR 2022, with a focus on Learning under limited/low resource scenarios. The main goal of PML4DC is to bring together researchers and practitioners (from academia, industry and government agencies) to reflect on aspects of designing, implementing, deploying and monitoring machine learning (ML) solutions that are typical in low resource environments across multiple sectors, such as healthcare, finance, agriculture, education and natural language processing. Specifically, we encourage contributions that highlight issues related to:
- Advances in algorithms and methods tailored for problems related with data-scarcity, imbalanced representations and limited computational resource
- Industry practices to scale-up ML solutions in low resource settings while balancing performance and latency trade-offs
- Societal and policy impacts of ML solutions in developing countries obtained via pilot studies, qualitative research, and human-in-the-loop settings.
Submission types
- Short papers and position pieces (up to 5 pages)
- Problem statements and abstracts (up to 2 page)
5-page submissions will be eligible for oral or poster presentation. 2-page submissions will be presented as posters. Page limit applies to content only, excluding references.
Submission Format
Contributions should be blinded and submitted using the ICLR template via CMT.
We have also included a brief guide on how to use the CMT template.
Ongoing work and papers that have appeared in a non-archival venue (workshops, arXiv, etc) are welcome. You may also submit work that has appeared in archival venues in 2020 or 2021. Please note that submissions are non-archival.
Important Dates
- Submission deadline: February 25, 2022
- Notification: March 25th, 2022
- Camera ready (Tentative): April 10th, 2022
- Workshop: April 29th, 2022
Organizers
Girmaw Abebe Tadesse (IBM Research)
Esube Bekele (In-Q-Tel)
Celia Cintas (IBM Research)
Timnit Gebru (DAIR)
Judy Gichoya (Emory University)
Meareg Hailemariam (Addis Ababa University)
Waheeda Saib (IBM Research)
More details: https://pml4dc.github.io/iclr2022/