25.8k citations · 44.3k across the 5 of their papers we have counts for
5 papers
Extracting Symptoms and their Status from Clinical Conversations
Nan Du, Kai Chen, Anjuli Kannan +3
This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status. Lack of any publicly…
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong +4
Current end-to-end machine reading and question answering (Q\&A) models are primarily based on recurrent neural networks (RNNs) with attention. Despite their success, these models…
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen +2
The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed vector representations that capture a large number of precise syntac…
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov, Kai Chen, Greg Corrado +1
We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a w…
Building high-level features using large scale unsupervised learning
Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga +5
We consider the problem of building high-level, class-specific feature detectors from only unlabeled data. For example, is it possible to learn a face detector using only unlabeled…