Deep Ensembles: A Loss Landscape Perspective

YouTube·Machine Learning

Explore the concept of deep ensembles from a loss landscape perspective in this 35-minute Launchpad talk. Delve into the hypothesis, background research, and methodologies used to measure function similarity within and across trajectories. Examine subspace sampling techniques and analyze loss and function similarity in prediction space. Evaluate the effects of ensembling and draw conclusions from the presented findings. Engage in a Q&A session to further discuss ideas and insights related to the arxiv.org paper 1912.02757.