activity
20122023
most citedCharacter-Aware Neural Language Models

1k citations · 3.4k across the 71 of their papers we have counts for

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Showing 2016 · stat.MLShow all

6 papers · 2 filters

stat.ML2016★ 14 cited

Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation

Yacine Jernite, Anna Choromanska, David Sontag

We consider multi-class classification where the predictor has a hierarchical structure that allows for a very large number of labels both at train and test time. The predictive po…

stat.ML2016★ 7 cited

Clinical Tagging with Joint Probabilistic Models

Yoni Halpern, Steven Horng, David Sontag

We describe a method for parameter estimation in bipartite probabilistic graphical models for joint prediction of clinical conditions from the electronic medical record. The method…

stat.ML2016★ 17 cited

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization

Shalmali Joshi, Suriya Gunasekar, David Sontag +1

This work proposes a new algorithm for automated and simultaneous phenotyping of multiple co-occurring medical conditions, also referred as comorbidities, using clinical notes from…

stat.ML2016

Structured Inference Networks for Nonlinear State Space Models

Rahul G. Krishnan, Uri Shalit, David Sontag

Gaussian state space models have been used for decades as generative models of sequential data. They admit an intuitive probabilistic interpretation, have a simple functional form,…

stat.ML2016★ 131 cited

Estimating individual treatment effect: generalization bounds and algorithms

Uri Shalit, Fredrik D. Johansson, David Sontag

There is intense interest in applying machine learning to problems of causal inference in fields such as healthcare, economics and education. In particular, individual-level causal…

stat.ML2016★ 185 cited

Learning Representations for Counterfactual Inference

Fredrik D. Johansson, Uri Shalit, David Sontag

Observational studies are rising in importance due to the widespread accumulation of data in fields such as healthcare, education, employment and ecology. We consider the task of a…