Efficient subsampling for linear regression under label budget

Neyman Seminar
Feb 15, 2017 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
We investigate statistical aspects of subsampling for large-scale linear regression under label budget constraints. In many applications, we have access to large datasets (such as healthcare records, database of building profiles, and visual stimuli), but the corresponding labels (such as customer satisfaction, energy usage, and brain response, respectively) are hard to obtain. We derive...
Aarti Singh, Machine Learning Department, Carnegie Mellon University