1. Opportunities for a More Interdisciplinary Approach to Perceptions of Fairness in Machine Learning Dasch, Sophia T., Rice, Vincent, Lakshminarayanan, Venkat R., Togu, Taiwo, Boykin, C Malik, and Brown, Sarah M. In NeurIPS 2020 Workshop: ML Retrospectives, Surveys & Meta-Analyses 2020
  2. Measuring Bias with Wasserstein Distance Kwekir-Aggrey, Kweku, and Brown, Sarah M In NeurIPS 2020 Workshop on Workshop on Dataset Curation and Security 2020
  3. Label Bias, Label Shift: Fair Machine Learning with Unreliable Labels Dai, Jessica, and Brown, Sarah M In Workshop on Consequential Decisions in Dynamic Environments NeurIPS 2020 2020
  4. Detecting Simpson’s Paradox Xu, Chenguang, Brown, Sarah M, and Grant, Christan AAAI FLAIRS 31 2018 [PDF]
  5. A Sparse Combined Regression-Classification Formulation for Learning a Physiological Alternative to Clinical Post-Traumatic Stress Disorder Scores Brown, Sarah M, Webb, Andrea, Mangoubi, Rami S, and Dy, Jennifer G In Association for the Advancement of Artificial Intelleigence 2015 2015
  6. Machine Learning Analysis of Peripheral Physiology for Emotion Detection Brown, Sarah M 2014
  7. Variety of Community Partnerships in Related Programs Brown, S.M. Sarah M, and Hulett, Mario M.A. In American Society for Engineering Education0 2013 [Abs]
  8. Technical Outreach Community Help : Initial Results Brown, S.M. Sarah M, and Thomas, L.D. Lauren D In American Society for Engineering Education 2011 [Abs]
  9. Technical Outreach Community Help : An Engineering Outreach-Mentoring Program For Minorities Thomas, Lauren D (Virginia Tech), Smith, Michael (National Society of Black Engineers), and Brown, Sarah In American Society for Engineering Education 2010 [Abs]