463 citations · 904 across the 24 of their papers we have counts for
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cs.LG2021★ 4 cited
Rank4Class: A Ranking Formulation for Multiclass Classification
Nan Wang, Zhen Qin, Le Yan +4
Multiclass classification (MCC) is a fundamental machine learning problem of classifying each instance into one of a predefined set of classes. In the deep learning era, extensive…
cs.IR2021★ 1 cited
Improving Neural Ranking via Lossless Knowledge Distillation
Zhen Qin, Le Yan, Yi Tay +4
We explore a novel perspective of knowledge distillation (KD) for learning to rank (LTR), and introduce Self-Distilled neural Rankers (SDR), where student rankers are parameterized…
cs.LG2021
Distilling Interpretable Models into Human-Readable Code
Walker Ravina, Ethan Sterling, Olexiy Oryeshko +5
The goal of model distillation is to faithfully transfer teacher model knowledge to a model which is faster, more generalizable, more interpretable, or possesses other desirable ch…