Miao Xu

Active Deep Learning to Tune Down the Noise in Labels

2018

The great success of supervised learning has initiated a paradigm shift from building a deterministic software system to a probabilistic artificial intelligent system throughout the industry. The historical records in enterprise domains can potentially bootstrap …

Provably Consistent Partial-Label Learning

2020 · Neural Information Processing Systems

Partial-label learning (PLL) is a multi-class classification problem, where each training example is associated with a set of candidate labels. Even though many practical PLL methods have been proposed in the last two decades, there …

A Boosting Algorithm for Positive-Unlabeled Learning

2022 · arXiv (Cornell University)

Positive-unlabeled (PU) learning deals with binary classification problems when only positive (P) and unlabeled (U) data are available. Many recent PU methods are based on neural networks, but little has been done to develop boosting …