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Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger



Zhiqi Bu , Yu-Xiang Wang , Sheng Zha , George Karypis


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Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning



Vishakh Padmakumar , Leonard Lausen , Miguel Ballesteros , Sheng Zha , He He , George Karypis

* Accepted to appear at NAACL 2022 

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Meta-learning via Language Model In-context Tuning



Yanda Chen , Ruiqi Zhong , Sheng Zha , George Karypis , He He


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Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes



Shuai Zheng , Haibin Lin , Sheng Zha , Mu Li

* Technical Report 

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Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual



He He , Sheng Zha , Haohan Wang


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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing



Jian Guo , He He , Tong He , Leonard Lausen , Mu Li , Haibin Lin , Xingjian Shi , Chenguang Wang , Junyuan Xie , Sheng Zha , Aston Zhang , Hang Zhang , Zhi Zhang , Zhongyue Zhang , Shuai Zheng


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Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources



Haibin Lin , Hang Zhang , Yifei Ma , Tong He , Zhi Zhang , Sheng Zha , Mu Li


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Question Type Guided Attention in Visual Question Answering



Yang Shi , Tommaso Furlanello , Sheng Zha , Animashree Anandkumar


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