2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2021★ 2 cited
Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff
Mitchell Naylor, Christi French, Samantha Terker +1
The healthcare domain is one of the most exciting application areas for machine learning, but a lack of model transparency contributes to a lag in adoption within the industry. In…
cs.LG2015
Theoretical and Empirical Analysis of a Parallel Boosting Algorithm
Uday Kamath, Carlotta Domeniconi, Kenneth De Jong
Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to…