280 citations · 387 across the 9 of their papers we have counts for
12 papers
Learning Predictive and Interpretable Timeseries Summaries from ICU Data
Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross +1
Machine learning models that utilize patient data across time (rather than just the most recent measurements) have increased performance for many risk stratification tasks in the i…
Evaluating the Interpretability of Generative Models by Interactive Reconstruction
Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang +2
For machine learning models to be most useful in numerous sociotechnical systems, many have argued that they must be human-interpretable. However, despite increasing interest in in…
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Slavin Ross, Finale Doshi-Velez
In representation learning, there has been recent interest in developing algorithms to disentangle the ground-truth generative factors behind a dataset, and metrics to quantify how…
Ensembles of Locally Independent Prediction Models
Andrew Slavin Ross, Weiwei Pan, Leo Anthony Celi +1
Ensembles depend on diversity for improved performance. Many ensemble training methods, therefore, attempt to optimize for diversity, which they almost always define in terms of di…
Learning Key-Value Store Design
Stratos Idreos, Niv Dayan, Wilson Qin +8
We introduce the concept of design continuums for the data layout of key-value stores. A design continuum unifies major distinct data structure designs under the same model. The cr…
Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack +19
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a po…