1 citations · 1 across the 1 of their papers we have counts for
4 papers
Evaluating representations by the complexity of learning low-loss predictors
William F. Whitney, Min Jae Song, David Brandfonbrener +2
We consider the problem of evaluating representations of data for use in solving a downstream task. We propose to measure the quality of a representation by the complexity of learn…
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
Kexin Huang, Jaan Altosaar, Rajesh Ranganath
Clinical notes contain information about patients that goes beyond structured data like lab values and medications. However, clinical notes have been underused relative to structur…
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji B. Dieng, Rajesh Ranganath, Jaan Altosaar +1
Recurrent neural networks (RNNs) are powerful models of sequential data. They have been successfully used in domains such as text and speech. However, RNNs are susceptible to overf…
Proximity Variational Inference
Jaan Altosaar, Rajesh Ranganath, David M. Blei
Variational inference is a powerful approach for approximate posterior inference. However, it is sensitive to initialization and can be subject to poor local optima. In this paper,…