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20182022
most citedToward Understanding Privileged Features Distillation in Learning-to-Rank

4 citations · 12 across the 5 of their papers we have counts for

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7 papers · 1 filter

cs.LG20224 cited

Toward Understanding Privileged Features Distillation in Learning-to-Rank

Shuo Yang, Sujay Sanghavi, Holakou Rahmanian +2

In learning-to-rank problems, a privileged feature is one that is available during model training, but not available at test time. Such features naturally arise in merchandised rec…

cs.LG20213 cited

Does Preprocessing Help Training Over-parameterized Neural Networks?

Zhao Song, Shuo Yang, Ruizhe Zhang

Deep neural networks have achieved impressive performance in many areas. Designing a fast and provable method for training neural networks is a fundamental question in machine lear…

cs.LG20213 cited

Speeding up Deep Model Training by Sharing Weights and Then Unsharing

Shuo Yang, Le Hou, Xiaodan Song +2

We propose a simple and efficient approach for training the BERT model. Our approach exploits the special structure of BERT that contains a stack of repeated modules (i.e., transfo…

cs.LG2021

Combinatorial Bandits without Total Order for Arms

Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon +1

We consider the combinatorial bandits problem, where at each time step, the online learner selects a size- subset from the arms set , where $\left|\mathcal{A}\r…

cs.LG20192 cited

Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space

Shuo Yang, Yanyao Shen, Sujay Sanghavi

Quadratic regression involves modeling the response as a (generalized) linear function of not only the features but also of quadratic terms . The inclusio…

cs.LG2018

Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data

Shuo Yang

With the expeditious advancement of information technologies, health-related data presented unprecedented potentials for medical and health discoveries but at the same time signifi…