We use a new general-purpose model of neutral evolution of genotypes to make quantitative comparisons of diversity and adaptive evolutionary activity as a function of mutation rate...
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
In this paper, we compare alternative techniques for evaluating a software system for simplifying the readability of texts for adults with mild intellectual disabilities (ID). We ...
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...