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Call For Papers

Resource constraints in developing countries can necessitate alternatives to conventional machine learning approaches. We invite submissions that address the following and related topic areas:

Algorithms and Methods

  • Methods for collecting and generating training data within data scarce (limited labeled data) settings (such as weak labels, model-based pre-labeling, teacher-student models, and transfer learning).
  • Machine learning techniques applied to limited data (e.g. active learning, few-shot and zero-shot learning).
  • Approaches to training and inference on resource constrained devices (such as model quantization, model compression, model distillation, low precision training, model pruning methods, and generalized model optimizations).
  • Alternative learning methods coupled with deep models targeted for low resources settings.
  • Automated techniques to stratify and valuate data in order to increase throughput in low-resource settings.
  • Analyse models in the perspective of fairness, explainability, etc.

Industry Experience and Applications

  • Data science and engineering practices that help balance accuracy/latency tradeoffs while scaling ML models in low resource environments.
  • Measuring success or impact that goes beyond algorithmic metrics (such as accuracy or F1 score).
  • Data-driven techniques that support public institutions (government transparency, healthcare, education etc).

Social and Policy Topics

  • Successful ML solution implementation stories which work at a small scale (e.g. local institution, city) that could be applied at larger scale.
  • Connecting skilled professionals with the organizations that deeply understand the local problems.
  • Securing funding for proof-of-concept (POC) projects or for scaling existing POCs.
  • Building effective research and implementation teams, with a focus on challenges specific to developing regions such as countries in Africa.
  • When machine learning is NOT a viable option.
  • Strategies and policies enabling or enhancing AI/ML adoptions for developing countries.

Instructions

Submission types

  • Short papers and position pieces (up to 5 pages)

  • Problem statements and abstracts (up to 2 page)

  • In addition, 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 an archival venues in 2022 or 2023. Please note that accepted papers at PML4LRS are non-archival.

Accepted Submissions

  • 5-page submissions will be eligible for oral or poster presentation.
  • 2-page submissions will be presented as posters. In both cases, page limit applies to content only, excluding references.

Submission Format and Link

Contributions should be anonymized and submitted using the ICLR template{:target="_blank" rel="noopener"} via Openreview. https://openreview.net/group?id=ICLR.cc/2024/Workshop/PML4LRS. We have also included a brief guide on how to use the CMT template.

Important Dates

  • Submissions deadline: February 09, 2024
  • Notification: February 27th, 2024
  • Camera ready: April 4th, 2024
  • Workshop: May 11th, 2024

Deadlines are at 11:59 PM AOE (AOE is anywhere on earth).