… , we test parallel solvers in a simple resilience framework with emulated silent errors. As in
previous … MACORD: online adaptive machine learning framework for silent error detection. In: …

… This paper shows an average error detection of 90% considering … an online adaptive SDC
detection algorithm using machine … exploration framework using machine learning supervised …

… [27] proposed a machine learning based detection method in terms of the AID … Cappello,
“Macord: Online adaptive machine learning framework for silent error detection,” in 2017 IEEE …

… Many types of software-based soft error detectors have been … [9], and detectors that fit a
machine learning model around the “… (DMR) can rigorously detect silent data corruptions by …

… Subasi O, Di S, Balaprakash P et al (2017) MACORD: online adaptive machine learning
framework for silent error detection. In: Proceedings of 2017 IEEE international conference on …

… A good example would be Silent Data Corruption (SDC) errors … detection methods have
been proposed such as Adaptive … -driven approaches via machine learning techniques can be …

… (DMR) can rigorously detect silent data corruptions by utilizing a … unlike those are generated
through machine learning [45… AID is an adaptive SDC detector wherein a best-fit prediction …

… It has also been adapted for other types of data, such as images and time series. It has …
RNN to develop an End-to-End deep learning framework for pose estimation. Authors used …

… from a limited amount of labelled data while adapting to new, unseen network behaviours. In
… Developing collaborative frameworks using deep learning to share knowledge and insights …

… –machine interaction while meeting the current industrial demands. In that process, machine
intelligence … is adapted. The nondeterministic algorithms try to overcome the probability of …