165 citations · 333 across the 19 of their papers we have counts for
6 papers · 1 filter
Prototypical Clustering Networks for Dermatological Disease Diagnosis
Viraj Prabhu, Anitha Kannan, Murali Ravuri +3
We consider the problem of image classification for the purpose of aiding doctors in dermatological diagnosis. Dermatological diagnosis poses two major challenges for standard off-…
Block Stability for MAP Inference
Hunter Lang, David Sontag, Aravindan Vijayaraghavan
To understand the empirical success of approximate MAP inference, recent work (Lang et al., 2018) has shown that some popular approximation algorithms perform very well when the in…
Evaluating Reinforcement Learning Algorithms in Observational Health Settings
Omer Gottesman, Fredrik Johansson, Joshua Meier +16
Much attention has been devoted recently to the development of machine learning algorithms with the goal of improving treatment policies in healthcare. Reinforcement learning (RL)…
Why Is My Classifier Discriminatory?
Irene Chen, Fredrik D. Johansson, David Sontag
Recent attempts to achieve fairness in predictive models focus on the balance between fairness and accuracy. In sensitive applications such as healthcare or criminal justice, this…
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson, Nathan Kallus, Uri Shalit +1
Predictive models that generalize well under distributional shift are often desirable and sometimes crucial to building robust and reliable machine learning applications. We focus…
Semi-Amortized Variational Autoencoders
Yoon Kim, Sam Wiseman, Andrew C. Miller +2
Amortized variational inference (AVI) replaces instance-specific local inference with a global inference network. While AVI has enabled efficient training of deep generative models…