We are excited to present a 5-day course on “Machine Learning Beyond Static Datasets” as part of the European Summer School on AI (ESSAI) in Ljubljana, Slovenia from July 24-28. Join the course to learn how to transcend the traditional static train-test machine learning focus and move all the way to the central elements underlying lifelong learning.
The more detailed course abstract is attached below, the description and schedule for a plethora of interesting other courses, together with the ESSAI registration can be found on the website: https://essai.si
Abstract: Machine learning studies the design of models and training algorithms in order to learn how to solve tasks from data. Whereas historically machine learning has concentrated primarily on static predefined training datasets and respective test scenarios, recent advances also take into account the fact that the world is constantly evolving. In this course, we will go beyond the train-validate-test phase and explore modern approaches to machines that can learn continually. In addition to a comprehensive overview of the breath of factors to consider in such continual learning, the course will outline the basics of techniques that span mitigation of forgetting across multiple tasks, selection of new data in ongoing training, and robustness with respect to unexpected data inputs.
