Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
In this paper we present Evaluate, a platform for learning performance monitoring. Evaluate manages a number of artefacts that can be used to monitor learning performance, like met...
Bernd Simon, Kasra Seirafi, Asmund Realfsen, Mark ...
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...