36 citations · 47 across the 3 of their papers we have counts for
3 papers
cs.LG2018★ 8 cited
Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
Hugh Chen, Scott Lundberg, Su-In Lee
Time series data constitutes a distinct and growing problem in machine learning. As the corpus of time series data grows larger, deep models that simultaneously learn features and…
cs.LG2017★ 3 cited
Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning
Gabriel Erion, Hugh Chen, Scott M. Lundberg +1
We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen)…
cs.LG2017★ 36 cited
Checkpoint Ensembles: Ensemble Methods from a Single Training Process
Hugh Chen, Scott Lundberg, Su-In Lee
We present the checkpoint ensembles method that can learn ensemble models on a single training process. Although checkpoint ensembles can be applied to any parametric iterative lea…