67 citations · 77 across the 3 of their papers we have counts for
3 papers
cs.GT2012★ 1 cited
On Calibrated Predictions for Auction Selection Mechanisms
H. Brendan McMahan, Omkar Muralidharan
Calibration is a basic property for prediction systems, and algorithms for achieving it are well-studied in both statistics and machine learning. In many applications, however, the…
stat.AP2012★ 9 cited
Detecting mutations in mixed sample sequencing data using empirical Bayes
Omkar Muralidharan, Georges Natsoulis, John Bell +2
We develop statistically based methods to detect single nucleotide DNA mutations in next generation sequencing data. Sequencing generates counts of the number of times each base wa…
stat.AP2010★ 67 cited
An empirical Bayes mixture method for effect size and false discovery rate estimation
Omkar Muralidharan
Many statistical problems involve data from thousands of parallel cases. Each case has some associated effect size, and most cases will have no effect. It is often important to est…