1 citations · 1 across the 2 of their papers we have counts for
4 papers
Causal Regularization
Dominik Janzing
I argue that regularizing terms in standard regression methods not only help against overfitting finite data, but sometimes also yield better causal models in the infinite sample r…
Clinical Concept Extraction for Document-Level Coding
Sarah Wiegreffe, Edward Choi, Sherry Yan +2
The text of clinical notes can be a valuable source of patient information and clinical assessments. Historically, the primary approach for exploiting clinical notes has been infor…
Causal Regularization
Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi +3
In application domains such as healthcare, we want accurate predictive models that are also causally interpretable. In pursuit of such models, we propose a causal regularizer to st…
Multi-layer Representation Learning for Medical Concepts
Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles +2
Learning efficient representations for concepts has been proven to be an important basis for many applications such as machine translation or document classification. Proper repres…