Conference on Lifelong Learning Agents

Aug 18 - 19, 2022 (Virtual)

Aug 22 - 24, 2022 (Montreal, Canada)

Machine learning has relied heavily on a traditional view of the learning process, whereby observations are assumed to be i.i.d., typically given as a dataset split into a training and validation set with the explicit focus to maximize performance on the latter. While this view proved to be immensely beneficial for the field, it represents just a fraction of the realistic scenarios of interest. Over the past few decades, increased attention has been given to alternative paradigms that help explore different aspects of the learning process, from Lifelong Learning, Continual Learning, and Meta-Learning to Transfer Learning, Multi-Task Learning and Out-Of-Distribution Generalization to name just a few.

The Conference on Lifelong Learning Agents (CoLLAs) focuses on these learning paradigms that aim to move beyond the traditional, single-distribution machine learning setting and to allow learning to be more robust, more efficient in terms of compute and data, more versatile in terms of being able to handle multiple problems and be well-defined and well-behaved in more realistic non-stationary settings compared to the traditional view.