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07/17/2023
Reflections from the Workshop on AI-Assisted Decision Making for Conservation
In this white paper, we synthesize key points made during presentations ...
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05/02/2023
Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy
Poverty maps derived from satellite imagery are increasingly used to inf...
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03/31/2023
Evaluation Challenges for Geospatial ML
As geospatial machine learning models and maps derived from their predic...
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11/16/2022
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?
Machine learning-based estimates of poverty and wealth are increasingly ...
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11/11/2022
Striving for data-model efficiency: Identifying data externalities on group performance
Building trustworthy, effective, and responsible machine learning system...
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02/28/2022
Resolving label uncertainty with implicit posterior models
We propose a method for jointly inferring labels across a collection of ...
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03/05/2021
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data
Collecting more diverse and representative training data is often touted...
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10/16/2020
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery
Combining satellite imagery with machine learning (SIML) has the potenti...
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03/15/2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
While real-world decisions involve many competing objectives, algorithmi...
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03/12/2020
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information
Observational data are often accompanied by natural structural indices, ...
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09/27/2018
A Successive-Elimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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03/12/2018
Delayed Impact of Fair Machine Learning
Fairness in machine learning has predominantly been studied in static cl...
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10/25/2017