no code implementations • 26 May 2020 • Kai Shu, Subhabrata Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah, Milad Shokouhi, Susan Dumais
In this paper, we propose to leverage user actions as a source of weak supervision, in addition to a limited set of annotated examples, to detect intents in emails.
no code implementations • 3 Jan 2020 • Xinyi Li, Chia-Jung Lee, Milad Shokouhi, Susan Dumais
Our approach starts with a reading time analysis based on the reading events from a major email platform, followed by a user study to provide explanations for some discoveries.
1 code implementation • 10 Nov 2019 • Guoqing Zheng, Ahmed Hassan Awadallah, Susan Dumais
We view the label correction procedure as a meta-process and propose a new meta-learning based framework termed MLC (Meta Label Correction) for learning with noisy labels.
Ranked #9 on Image Classification on Clothing1M (using clean data) (using extra training data)
no code implementations • 24 Oct 2019 • Kai Shu, Ahmed Hassan Awadallah, Susan Dumais, Huan Liu
This is especially the case for many real-world tasks where large scale annotated examples are either too expensive to acquire or unavailable due to privacy or data access constraints.