activity
20202026
most citedGeneralized and Scalable Optimal Sparse Decision Trees

41 citations · 47 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors

Di Hu, Kun Li, Haojie Rao +6

Accurate prediction of molecular properties underpins drug discovery and material design, yet even state-of-the-art models remain vulnerable to localized failure modes that aggrega…

cs.LG2023★ 2 cited

Supervised Knowledge May Hurt Novel Class Discovery Performance

Ziyun Li, Jona Otholt, Ben Dai +3

Novel class discovery (NCD) aims to infer novel categories in an unlabeled dataset by leveraging prior knowledge of a labeled set comprising disjoint but related classes. Given tha…

cs.CV2022★ 2 cited

A Closer Look at Novel Class Discovery from the Labeled Set

Ziyun Li, Jona Otholt, Ben Dai +3

Novel class discovery (NCD) aims to infer novel categories in an unlabeled dataset leveraging prior knowledge of a labeled set comprising disjoint but related classes. Existing res…

cs.LG2021★ 2 cited

Not All Knowledge Is Created Equal: Mutual Distillation of Confident Knowledge

Ziyun Li, Xinshao Wang, Di Hu +4

Mutual knowledge distillation (MKD) improves a model by distilling knowledge from another model. However, \textit{not all knowledge is certain and correct}, especially under advers…

cs.LG2020★ 41 cited

Generalized and Scalable Optimal Sparse Decision Trees

Jimmy Lin, Chudi Zhong, Diane Hu +2

Decision tree optimization is notoriously difficult from a computational perspective but essential for the field of interpretable machine learning. Despite efforts over the past 40…