This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...
We present a self-valuing learning technique which is capable of learning how to grasp unfamiliar objects and generalize the learned abilities. The learning system consists of two...
We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
In the recent development ofwrious models of learning inspired by the PAC learning model (introduced by Valiant) there has been a trend towards models which are as representation ...