Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
Abstract. This paper describes a visual localization approach for mobile robots. Robot localization is performed as location recognition. The approach uses global visual features (...
Olivier Saurer, Friedrich Fraundorfer, Marc Pollef...
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...