We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
This paper reports two experiments with implementations of constructions from theoretical computer science. The first one deals with Kleene’s and Rogers’ second recursion the...
Torben Amtoft Hansen, Thomas Nikolajsen, Jesper La...
The advantages of pattern-based programming have been well-documented in the sequential literature. However patterns have yet to make their way into mainstream parallel computing,...
Steven Bromling, Steve MacDonald, John Anvik, Jona...
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...