2 citations · 3 across the 3 of their papers we have counts for
3 papers
stat.ME2022★ 1 cited
Wasserstein Distributional Learning
Chengliang Tang, Nathan Lenssen, Ying Wei +1
Learning conditional densities and identifying factors that influence the entire distribution are vital tasks in data-driven applications. Conventional approaches work mostly with…
cs.CV2021★ 2 cited
Artificial Perceptual Learning: Image Categorization with Weak Supervision
Chengliang Tang, María Uriarte, Helen Jin +2
Machine learning has achieved much success on supervised learning tasks with large sets of well-annotated training samples. However, in many practical situations, such strong and h…
stat.ML2021
Weakly Supervised Learning Creates a Fusion of Modeling Cultures
Chengliang Tang, Gan Yuan, Tian Zheng
The past two decades have witnessed the great success of the algorithmic modeling framework advocated by Breiman et al. (2001). Nevertheless, the excellent prediction performance o…