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@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2002.02112, | |
title = {Unbalanced GANs: Pre-training the Generator of Generative Adversarial | |
Network using Variational Autoencoder}, | |
author = {Hyungrok Ham , Tae Joon Jun , Daeyoung Kim}, | |
journal={arXiv preprint arXiv:2002.02112}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2002.02112v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2002.02112, | |
title = {Unbalanced GANs: Pre-training the Generator of Generative Adversarial | |
Network using Variational Autoencoder}, | |
author = {Hyungrok Ham , Tae Joon Jun , Daeyoung Kim}, | |
journal={arXiv preprint arXiv:2002.02112}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2002.02112v1} | |
} | |
@article{1904.08994, | |
title = {From GAN to WGAN}, | |
author = {Lilian Weng}, | |
journal={arXiv preprint arXiv:1904.08994}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.08994v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2002.02112, | |
title = {Unbalanced GANs: Pre-training the Generator of Generative Adversarial | |
Network using Variational Autoencoder}, | |
author = {Hyungrok Ham , Tae Joon Jun , Daeyoung Kim}, | |
journal={arXiv preprint arXiv:2002.02112}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2002.02112v1} | |
} | |
@article{1904.08994, | |
title = {From GAN to WGAN}, | |
author = {Lilian Weng}, | |
journal={arXiv preprint arXiv:1904.08994}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.08994v1} | |
} | |
@article{1904.00724, | |
title = {GAN You Do the GAN GAN?}, | |
author = {Joseph Suarez}, | |
journal={arXiv preprint arXiv:1904.00724}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.00724v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2002.02112, | |
title = {Unbalanced GANs: Pre-training the Generator of Generative Adversarial | |
Network using Variational Autoencoder}, | |
author = {Hyungrok Ham , Tae Joon Jun , Daeyoung Kim}, | |
journal={arXiv preprint arXiv:2002.02112}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2002.02112v1} | |
} | |
@article{1904.08994, | |
title = {From GAN to WGAN}, | |
author = {Lilian Weng}, | |
journal={arXiv preprint arXiv:1904.08994}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.08994v1} | |
} | |
@article{1904.00724, | |
title = {GAN You Do the GAN GAN?}, | |
author = {Joseph Suarez}, | |
journal={arXiv preprint arXiv:1904.00724}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.00724v1} | |
} | |
@article{1607.01664, | |
title = {Personalized Optimization for Computer Experiments with Environmental | |
Inputs}, | |
author = {Shifeng Xiong}, | |
journal={arXiv preprint arXiv:1607.01664}, | |
year = {2016}, | |
url = {http://arxiv.org/abs/1607.01664v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
author = {Zhiyuan Zhang , Wei Li , Ruihan Bao , Keiko Harimoto , Yunfang Wu , Xu Sun}, | |
journal={arXiv preprint arXiv:2108.08976}, | |
year = {2021}, | |
url = {http://arxiv.org/abs/2108.08976v2} | |
} | |
@article{2010.05244, | |
title = {Advanced Dropout: A Model-free Methodology for Bayesian Dropout | |
Optimization}, | |
author = {Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo}, | |
journal={arXiv preprint arXiv:2010.05244}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2010.05244v2} | |
} | |
@article{1911.12675, | |
title = {Continuous Dropout}, | |
author = {Xu Shen , Xinmei Tian , Tongliang Liu , Fang Xu , Dacheng Tao}, | |
journal={arXiv preprint arXiv:1911.12675}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1911.12675v1} | |
} | |
@article{2212.14149, | |
title = {Macro-block dropout for improved regularization in training end-to-end | |
speech recognition models}, | |
author = {Chanwoo Kim , Sathish Indurti , Jinhwan Park , Wonyong Sung}, | |
journal={arXiv preprint arXiv:2212.14149}, | |
year = {2022}, | |
url = {http://arxiv.org/abs/2212.14149v1} | |
} | |
@article{1805.10896, | |
title = {Adaptive Network Sparsification with Dependent Variational | |
Beta-Bernoulli Dropout}, | |
author = {Juho Lee , Saehoon Kim , Jaehong Yoon , Hae Beom Lee , Eunho Yang , Sung Ju Hwang}, | |
journal={arXiv preprint arXiv:1805.10896}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.10896v3} | |
} | |
@article{2004.13342, | |
title = {Scheduled DropHead: A Regularization Method for Transformer Models}, | |
author = {Wangchunshu Zhou , Tao Ge , Ke Xu , Furu Wei , Ming Zhou}, | |
journal={arXiv preprint arXiv:2004.13342}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2004.13342v2} | |
} | |
@article{1805.08355, | |
title = {Opening the black box of deep learning}, | |
author = {Dian Lei , Xiaoxiao Chen , Jianfei Zhao}, | |
journal={arXiv preprint arXiv:1805.08355}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1805.08355v1} | |
} | |
@article{1806.01756, | |
title = {Concept-Oriented Deep Learning}, | |
author = {Daniel T Chang}, | |
journal={arXiv preprint arXiv:1806.01756}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1806.01756v1} | |
} | |
@article{1908.02130, | |
title = {Deep learning research landscape & roadmap in a nutshell: past, present | |
and future -- Towards deep cortical learning}, | |
author = {Aras R. Dargazany}, | |
journal={arXiv preprint arXiv:1908.02130}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.02130v1} | |
} | |
@article{1812.05448, | |
title = {A First Look at Deep Learning Apps on Smartphones}, | |
author = {Mengwei Xu , Jiawei Liu , Yuanqiang Liu , Felix Xiaozhu Lin , Yunxin Liu , Xuanzhe Liu}, | |
journal={arXiv preprint arXiv:1812.05448}, | |
year = {2018}, | |
url = {http://arxiv.org/abs/1812.05448v4} | |
} | |
@article{2303.15533, | |
title = {Sequential training of GANs against GAN-classifiers reveals correlated | |
"knowledge gaps" present among independently trained GAN instances}, | |
author = {Arkanath Pathak , Nicholas Dufour}, | |
journal={arXiv preprint arXiv:2303.15533}, | |
year = {2023}, | |
url = {http://arxiv.org/abs/2303.15533v1} | |
} | |
@article{2002.02112, | |
title = {Unbalanced GANs: Pre-training the Generator of Generative Adversarial | |
Network using Variational Autoencoder}, | |
author = {Hyungrok Ham , Tae Joon Jun , Daeyoung Kim}, | |
journal={arXiv preprint arXiv:2002.02112}, | |
year = {2020}, | |
url = {http://arxiv.org/abs/2002.02112v1} | |
} | |
@article{1904.08994, | |
title = {From GAN to WGAN}, | |
author = {Lilian Weng}, | |
journal={arXiv preprint arXiv:1904.08994}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.08994v1} | |
} | |
@article{1904.00724, | |
title = {GAN You Do the GAN GAN?}, | |
author = {Joseph Suarez}, | |
journal={arXiv preprint arXiv:1904.00724}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1904.00724v1} | |
} | |
@article{1607.01664, | |
title = {Personalized Optimization for Computer Experiments with Environmental | |
Inputs}, | |
author = {Shifeng Xiong}, | |
journal={arXiv preprint arXiv:1607.01664}, | |
year = {2016}, | |
url = {http://arxiv.org/abs/1607.01664v1} | |
} | |
@article{1908.05689, | |
title = {Stochastic Polynomial Optimization}, | |
author = {Jiawang Nie , Liu Yang , Suhan Zhong}, | |
journal={arXiv preprint arXiv:1908.05689}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1908.05689v1} | |
} | |
@article{2108.08976, | |
title = {ASAT: Adaptively Scaled Adversarial Training in Time Series}, | |
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