Yan-Long Huang

Fast Non-Parametric Heteroscedastic Imitation Learning With Geometric Priors

When learning probabilistic policies from human demonstrations, data-efficient learning and fast adaptations to new scenarios are key requirements. One popular way to achieve intuitive and reliable adaptations is through non-parametric, typically kernel-based, methods. However, existing solutions either fail to account...