17 citations · 55 across the 12 of their papers we have counts for
3 papers · 1 filter
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery
Esther Rolf, Jonathan Proctor, Tamma Carleton +5
Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-po…
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information
Esther Rolf, Michael I. Jordan, Benjamin Recht
Observational data are often accompanied by natural structural indices, such as time stamps or geographic locations, which are meaningful to prediction tasks but are often discarde…
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf, Max Simchowitz, Sarah Dean +4
While real-world decisions involve many competing objectives, algorithmic decisions are often evaluated with a single objective function. In this paper, we study algorithmic polici…