The goal of this paper is to improve the prediction performance of fault-prone module prediction models (fault-proneness models) by employing over/under sampling methods, which ar...
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
Motivated by a machine learning perspective—that gametheoretic equilibria constraints should serve as guidelines for predicting agents’ strategies, we introduce maximum causal...
— We present a tool, PerfCenter, that takes as input the deployment, configuration, message flow and workload details of the hardware and software servers in an application hos...
Autonomic Computing is now showing its value as a solution to the increased complexities of maintaining computer systems and has been applied to many different fields. In this pap...