Haw-minn Lu
Dr. Haw-minn Lu is currently a Principal Data Scientist for Data Science/Machine Learning at West Health Institute in La Jolla, a nonprofit medical research organization. Dr. Lu earned his PhD in 1998 from the Electrical and Computer Engineering Department at the University of California, San Diego after receiving SM and SB degrees from the Massachusetts Institute of Technology.
Dr. Lu has been doing machine learning for over 25 years. His interests include machine learning, interactive visualization, data imputation/anonymization, and computing infrastructure.
Prior to joining West Health, Dr. Lu was involved in several startups using Python as the core infrastructure for applications such as ecommerce, network communications, and digital animation.
Sessions
Machine learning algorithms, especially artificial neural networks, are not tolerant of missing data. Many practitioners simply remove records with missing fields without any consideration for the potential statistical bias that might be introduced. The field of imputation has become mature with imputations not only predicting missing values, but reflecting the uncertainty in the prediction. Traditional statistical estimators make use of the full benefits offered by advanced imputation techniques. This tutorial illustrates techniques and architectures that can incorporate advanced imputation techniques into machine learning pipelines including artificial neural networks.