Abstract. Predictive analysis aims at detecting concurrency errors during runtime by monitoring a concrete execution trace of a concurrent program. In recent years, various models ...
Chao Wang, Sudipta Kundu, Malay K. Ganai, Aarti Gu...
The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total...
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Automatic management of large-scale production systems requires a continuous monitoring service to keep track of the states of the managed system. However, it is challenging to ac...
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...