This paper presents a novel end-to-end approach to program repair based on sequence-to-sequence learning. We devise, implement, and evaluate system, called SequenceR, for fixing bugs learning source code. uses the copy mechanism overcome unlimited vocabulary problem that occurs with big Our system is data-driven; we train it 35,578 samples, carefully curated from commits open-source repositorie...

Clustered multi-task learning, which aims to leverage the generalization performance over clustered tasks, has shown an outstanding in various machine learning applications. In this paper, a sequence-to-sequence (CMSL) for autonomous vehicle systems (AVSs) large-scale semiconductor fabrications (fab) is proposed, where AVSs are widely used wafer transfers. Recently, as fabs become larger, repos...

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the f...