Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known lab...
Alex J. Smola, Novi Quadrianto, Quoc V. Le, Tib&ea...
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Background: In genetic transcription research, gene expression is typically reported in a test sample relative to a reference sample. Laboratory assays that measure gene expressio...
Behavioral Signal Processing aims at automating behavioral coding schemes such as those prevalent in psychology and mental health research. This paper describes methods to quantif...
Viktor Rozgic, Bo Xiao, Athanasios Katsamanis, Bri...