Sheng Zha

According to our database, Sheng Zha authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Pre-training Differentially Private Models with Limited Public Data.

Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis

CoRR, 2024

Extreme Miscalibration and the Illusion of Adversarial Robustness.

Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis

CoRR, 2024

2023

Zero redundancy distributed learning with differential privacy.

Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis

CoRR, 2023

On the accuracy and efficiency of group-wise clipping in differentially private optimization.

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

CoRR, 2023

Coupling public and private gradient provably helps optimization.

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

CoRR, 2023

Large Language Models of Code Fail at Completing Code with Potential Bugs.

Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

HyTrel: Hypergraph-enhanced Tabular Data Representation Learning.

Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Optimization on Large Model at Small Cost.

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

Proceedings of the International Conference on Machine Learning, 2023

Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.

Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion.

Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic.

Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, Leonard Lausen, Sheng Zha, Saab Mansour

CoRR, 2022

Differentially Private Bias-Term only Fine-tuning of Foundation Models.

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

CoRR, 2022

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

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

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Meta-learning via Language Model In-context Tuning.

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

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing.

Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis

Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, 2021

2020

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, Yi Zhu

J. Mach. Learn. Res., 2020

Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes.

Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li

CoRR, 2020

2019

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

CoRR, 2019

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

CoRR, 2019

Just-in-Time Dynamic-Batching.

Sheng Zha, Ziheng Jiang, Haibin Lin, Zhi Zhang

CoRR, 2019

Dive into Deep Learning for Natural Language Processing.

Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual.

He He, Sheng Zha, Haohan Wang

Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019

2018

Question Type Guided Attention in Visual Question Answering.

Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar

Proceedings of the Computer Vision - ECCV 2018, 2018