Search Results for author: Susan Dumais

Found 4 papers, 1 papers with code

Learning with Weak Supervision for Email Intent Detection

no code implementations26 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.

Intent Classification Intent Detection

Characterizing Reading Time on Enterprise Emails

no code implementations3 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.

Meta Label Correction for Noisy Label Learning

1 code implementation10 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 #6 on Image Classification on Clothing1M (using clean data) (using extra training data)

Learning with noisy labels Meta-Learning +1

Detecting Fake News with Weak Social Supervision

no code implementations24 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.

Fake News Detection

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