1 citations · 1 across the 1 of their papers we have counts for
3 papers
stat.ML2020
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference
Disi Ji, Padhraic Smyth, Mark Steyvers
We investigate the problem of reliably assessing group fairness when labeled examples are few but unlabeled examples are plentiful. We propose a general Bayesian framework that can…
stat.ML2020
Active Bayesian Assessment for Black-Box Classifiers
Disi Ji, Robert L. Logan, Padhraic Smyth +1
Recent advances in machine learning have led to increased deployment of black-box classifiers across a wide variety of applications. In many such situations there is a critical nee…
stat.ML2017★ 1 cited
Mondrian Processes for Flow Cytometry Analysis
Disi Ji, Eric Nalisnick, Padhraic Smyth
Analysis of flow cytometry data is an essential tool for clinical diagnosis of hematological and immunological conditions. Current clinical workflows rely on a manual process calle…