Abstract: Large pre-trained models trained on internet-scale data are often not ready for safe deployment out of the box. They are heavily fine-tuned and aligned using large quantities of human preference data. When we want to align an AI/ML model to human preference or values, it is worthwhile to ask …
Machine learning algorithms for policy and decision making are becoming ubiquitous. In many societal applications, the inferences we can draw are often severely limited not by the number of subjects in the data but rather by limited observations available for each subject. My research focuses on tackling these limitations both …
Machine learning algorithms for policy and decision making are becoming ubiquitous. In many societal applications, the inferences we can draw are often severely limited not by the number of subjects in the data but rather by limited observations available for each subject. My research focuses on tackling these limitations both …