Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results

Semi-supervised learning is the learning setting in which we have both labeled and unlabeled data at our disposal. This survey covers theoretical results for this setting and maps out the benefits of unlabeled data in classification and regression tasks. Most methods that use unlabeled data rely on certain assumptions about the data...

LaSeSOM: A Latent and Semantic Representation Framework for Soft Object Manipulation

Soft object manipulation has recently gained popularity within the robotics community due to its potential applications in many economically important areas. Although great progress has been recently achieved in these types of tasks, most state-of-the-art methods are case-specific; They can only be used to perform a single deformation task (e...