Publications

1. Y Li, M De-Arteaga, M Saar-Tsechansky, “When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias”, the AAAI Conference on Human Computation and Crowdsourcing, 2022, Link
2. Y Wang, A Wang, Z Liu, A Thurman, L Powers, M Zou, A Hefel, Y Li, J Zabner, K.F. Au,”Single-molecule Long-read Sequencing Reveals the Chromatin Basis of Gene Expression” Genome Research, 2019. Link
3. Y Li, T Wang, “Next Hit Predictor-Self-exciting Risk Modeling for Predicting Next Locations of Serial Crimes”, AI for Social Good Workshop NeurIPS 2018. Link

Work in progress

1. T Wang, J Yang, Y Li, B Wang, “Partially interpretable estimators (PIE): black-box-refined interpretable machine learning” Link
2. S Srivastava, Z Xu, Y Li, N Street, S Gilbertson-White, “Gaussian Process Regression and Classification using International Classification of Disease Codes as Covariates” Link