3 citations · 4 across the 2 of their papers we have counts for
3 papers
An Exploration of Active Learning for Affective Digital Phenotyping
Peter Washington, Cezmi Mutlu, Aaron Kline +9
Some of the most severe bottlenecks preventing widespread development of machine learning models for human behavior include a dearth of labeled training data and difficulty of acqu…
Classifying Autism from Crowdsourced Semi-Structured Speech Recordings: A Machine Learning Approach
Nathan A. Chi, Peter Washington, Aaron Kline +5
Autism spectrum disorder (ASD) is a neurodevelopmental disorder which results in altered behavior, social development, and communication patterns. In past years, autism prevalence…
Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels
Peter Washington, Onur Cezmi Mutlu, Emilie Leblanc +8
Emotion classifiers traditionally predict discrete emotions. However, emotion expressions are often subjective, thus requiring a method to handle subjective labels. We explore the…