This paper discusses how conventional testing criteria such as branch coverage can be applied for the testing of member functions inside a class. To support such testing technique...
In Sang Chung, Malcolm Munro, Wan Kwon Lee, Yong R...
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
We propose a novel approach, called Dynamic Fractional Resource Scheduling (DFRS), to share homogeneous cluster computing platforms among competing jobs. DFRS leverages virtual mac...
Rootkits are used by malicious attackers who desire to run software on a compromised machine without being detected. They have become stealthier over the years as a consequence of...
Francis M. David, Ellick Chan, Jeffrey C. Carlyle,...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...