Workshop on Learning-augmented Algorithms: Theory and Applications (LATA), ACM SIGMETRICS 2026:
This workshop aims to provide a platform for discussing recent results, as well as emerging directions in the rapidly-advancing field of learning-augmented algorithms, also known as algorithms with predictions. We solicit two types of posters: posters presenting new ideas, works in progress, ongoing research directions, and preliminary results; and posters describing recently published papers on related topics.

Important Dates:
Submission deadline: April 1, 2026

Notification of poster acceptance: April 15, 2026

Submission Requirements and Guidelines:
Submissions should consist of a 2-page abstract (not including references) using the PER template. The submission should include the names and affiliations of the contributors, a title, a brief abstract, and a summary of the contributions. Submissions must be in PDF format. If there are any questions, please contact Bo Sun (bo.sun@uottawa.ca) or Nico Christianson (christianson@stanford.edu).

Welcome to the Workshop on Learning-augmented Algorithms: Theory and Applications (LATA) (LATA 2026) submissions site. For general information, see https://learning-augmented-algorithms.github.io/.

Submissions

Submissions are currently closed.