Visual Representation Learning for Preference-Aware Path Planning

no code implementations • 18 Sep 2021 • Kavan Singh Sikand, Sadegh Rabiee, Adam Uccello, Xuesu Xiao, Garrett Warnell, Joydeep Biswas

We introduce Visual Representation Learning for Preference-Aware Path Planning (VRL-PAP), an alternative approach that overcomes all three limitations: VRL-PAP leverages unlabeled human demonstrations of navigation to autonomously generate triplets for learning visual representations of terrain that are viewpoint invariant and encode terrain types in a continuous representation space.

Representation Learning Semantic Segmentation

Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces

no code implementations • 7 Oct 2019 • Santiago Hernández-Orozco, Hector Zenil, Jürgen Riedel, Adam Uccello, Narsis A. Kiani, Jesper Tegnér

We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research.

BIG-bench Machine Learning General Classification +2