Active learning improves training efficiency by selectively querying the most informative samples for labeling. While it naturally fits classification tasks–where informative …
Proposes a new active learning approach by proposing a new uncertainty measure called the least disagree metric, as well as its efficient estimator, which is proven to be …
Proposes a new MMD-based definition of fairness for PCA, then formulate fair PCA as an optimization over the Stiefel manifold. Various theoretical and empirical discussions show …
