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Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

S. Huang, D. Xu, I. Yen, Y. Wang, S. Chang, B. Li, S. Chen, M. Xie, S. Rajasekaran, H. Liu, and C. Ding. ACL (1), page 190-200. Association for Computational Linguistics, (2022)

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En-Chul Chang

In-Sung Chang

Sung Pil Chang

Yu-Sung Chang

Chang-Sung Lim

Other publications of authors with the same name

Hardware-efficient stochastic rounding unit design for DNN training: late breaking results.S. Chang, G. Yuan, A. Lu, M. Sun, Y. Li, X. Ma, Z. Li, Y. Xie, M. Qin, X. Lin and 2 other author(s). DAC, page 1396-1397. ACM, (2022)FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization.M. Sun, Z. Li, A. Lu, Y. Li, S. Chang, X. Ma, X. Lin, and Z. Fang. FPGA, page 134-145. ACM, (2022)MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization.I. Yen, W. Lee, K. Zhong, S. Chang, P. Ravikumar, and S. Lin. NeurIPS, page 10891-10899. (2018)SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits.Y. Xie, P. Dong, G. Yuan, Z. Li, M. Zabihi, C. Wu, S. Chang, X. Zhang, X. Lin, C. Ding and 3 other author(s). DATE, page 1-6. IEEE, (2024)RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions.S. Chang, Y. Li, M. Sun, W. Jiang, S. Liu, Y. Wang, and X. Lin. ICCV, page 5231-5240. IEEE, (2021)Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework.S. Chang, Y. Li, M. Sun, R. Shi, H. So, X. Qian, Y. Wang, and X. Lin. HPCA, page 208-220. IEEE, (2021)Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.S. Huang, D. Xu, I. Yen, Y. Wang, S. Chang, B. Li, S. Chen, M. Xie, S. Rajasekaran, H. Liu and 1 other author(s). ACL (1), page 190-200. Association for Computational Linguistics, (2022)You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding.G. Yuan, S. Chang, Q. Jin, A. Lu, Y. Li, Y. Wu, Z. Kong, Y. Xie, P. Dong, M. Qin and 4 other author(s). ECCV (12), volume 13672 of Lecture Notes in Computer Science, page 34-51. Springer, (2022)Latent Feature Lasso.I. Yen, W. Lee, S. Chang, A. Suggala, S. Lin, and P. Ravikumar. ICML, volume 70 of Proceedings of Machine Learning Research, page 3949-3957. PMLR, (2017)Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework.S. Chang, Y. Li, M. Sun, R. Shi, H. So, X. Qian, Y. Wang, and X. Lin. CoRR, (2020)

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Disambiguation of "Chang, Sung-En"

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Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Please choose a person to relate this publication to

En-Chul Chang

In-Sung Chang

Sung Pil Chang

Yu-Sung Chang

Chang-Sung Lim

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Chang, Sung-En"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Please choose a person to relate this publication to

En-Chul Chang

In-Sung Chang

Sung Pil Chang

Yu-Sung Chang

Chang-Sung Lim

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
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Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.