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Joining datasets via data augmentation in the label space for neural networks


Jun 17, 2021
Jake Zhao, Mingfeng Ou, Linji Xue, Yunkai Cui, Sai Wu, Gang Chen

* Accepted in ICML 2021. Jake Zhao and Mingfeng Ou contributed equally 

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A critical look at the current train/test split in machine learning


Jun 08, 2021
Jimin Tan, Jianan Yang, Sai Wu, Gang Chen, Jake Zhao


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Levenshtein Transformer


May 27, 2019
Jiatao Gu, Changhan Wang, Jake Zhao

* 16 pages (6 pages appendix). Work in progress 

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GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations


Jul 02, 2018
Zhilin Yang, Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun


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Adversarially Regularized Autoencoders


Jun 29, 2018
Jake Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun

* ICML 2018 

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Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples


Feb 26, 2018
Jake Zhao, Kyunghyun Cho


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End to End Learning for Self-Driving Cars


Apr 25, 2016
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, Karol Zieba


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