Jun Xie

ML-LRC: Low-rank-constraint-based Multi-label Learning with Label Noise

2020 · 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

Existing multi-label learning algorithms mostly assume that all class labels in an obtained data set are completely accurate. This assumption is rarely valid. As the scale of the label space increases, owing to limited domain …

Regularizing End-to-End Speech Translation with Triangular Decomposition Agreement

2021 · arXiv (Cornell University)

End-to-end speech-to-text translation (E2E-ST) is becoming increasingly popular due to the potential of its less error propagation, lower latency, and fewer parameters. Given the triplet training corpus $\langle speech, transcription, translation\rangle$, the conventional high-quality E2E-ST …

Deep Semantic Role Labeling With Self-Attention

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Semantic Role Labeling (SRL) is believed to be a crucial step towards natural language understanding and has been widely studied. Recent years, end-to-end SRL with recurrent neural networks (RNN) has gained increasing attention. However, it …