1.1k citations · 5.4k across the 59 of their papers we have counts for
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A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
Decision trees are important both as interpretable models amenable to high-stakes decision-making, and as building blocks of ensemble methods such as random forests and gradient bo…
Towards Robust Waveform-Based Acoustic Models
Dino Oglic, Zoran Cvetkovic, Peter Sollich +2
We study the problem of learning robust acoustic models in adverse environments, characterized by a significant mismatch between training and test conditions. This problem is of pa…
Interpreting and improving deep-learning models with reality checks
Chandan Singh, Wooseok Ha, Bin Yu
Recent deep-learning models have achieved impressive predictive performance by learning complex functions of many variables, often at the cost of interpretability. This chapter cov…
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting
Bin Yu, Chandan Singh
In this article, we take a step back to distill seven principles out of our experience in the spring of 2020, when our 12-person rapid-response team used skills of data science and…