Search Results for author:
Found 8 papers, 4 papers with code
Assessing Phenotype Definitions for Algorithmic Fairness
While there are multiple potential sources of bias when constructing phenotype definitions which may affect their fairness, it is not standard in the field of phenotyping to consider the impact of different definitions across subgroups of patients.
Evaluating representations by the complexity of learning low-loss predictors
We consider the problem of evaluating representations of data for use in solving a downstream task.
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
Clinical notes contain information about patients that goes beyond structured data like lab values and medications.
Noisin: Unbiased Regularization for Recurrent Neural Networks
On the Penn Treebank, the method with Noisin more quickly reaches state-of-the-art performance.
Noise-Based Regularizers for Recurrent Neural Networks
We develop a noise-based regularization method for RNNs.
Proximity Variational Inference
Consequently, PVI is less sensitive to initialization and optimization quirks and finds better local optima.
Operator Variational Inference
Though this divergence has been widely used, the resultant posterior approximation can suffer from undesirable statistical properties.
Fast, Flexible Models for Discovering Topic Correlation across Weakly-Related Collections
Weak topic correlation across document collections with different numbers of topics in individual collections presents challenges for existing cross-collection topic models.
