2 papers
cs.RO2026
AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning
Hang Yin, Yinan Liang, Jiazhao Zhang +4
Lifelong embodied navigation in dynamic environments requires robots to form persistent scene understanding from fragmentary observations, which remains difficult for existing meth…
cs.LG2024
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks
Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco +3
Given a finite set of sample points, meta-learning algorithms aim to learn an optimal adaptation strategy for new, unseen tasks. Often, this data can be ambiguous as it might belon…