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Transfer learning is an important approach that produces pre-trained teacher models which can be used to quickly build specialized student models.
The mnist database of handwritten digits
Y. LeCun · 1998
Earlier work this paper cites.
Introduction to the Calculus of Variations
B. Dacorogna · 2004
Earlier work this paper cites.
What Regularized Auto-Encoders Learn from the Data-Generating Distribution
G. Alain and Y. Bengio · 2014
Earlier work this paper cites.
Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing
M. Fredrikson, E. Lantz, S. Jha, S. Lin, D. Page, and T. Ristenpart · 2014
Earlier work this paper cites.
A data-driven approach to cleaning large face datasets
H.-W. Ng and S. Winkler · 2014
Earlier work this paper cites.
Model Inversion Attacks That Exploit Confidence Information and Basic Countermeasures
M. Fredrikson, S. Jha, and T. Ristenpart · 2015
Earlier work this paper cites.
Deep Learning Face Attributes in the Wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Earlier work this paper cites.
A self-adaptive strategy for evolution of cooperation in distributed networks
D. Ye and M. Zhang · 2015
Earlier work this paper cites.
A Survey of Transfer Learning
K. Weiss, T. M. Khoshgoftaar, and D. Wang · 2016
Earlier work this paper cites.
Learning Deep Features for Discriminative Localization
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2016
Earlier work this paper cites.
Interpretable Explanations of Black Boxes by Meaningful Perturbation
R. C. Fong and A. Vedaldi · 2017
Earlier work this paper cites.
Adversarial Examples in the Physical World
A. Kurakin, I. J. Goodfellow, and S. Bengio · 2017
Earlier work this paper cites.
Membership Inference Attacks against Machine Learning Models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
Earlier work this paper cites.
Model-Reuse Attacks on Deep Learning Systems
Y. Ji, X. Zhang, S. Ji, X. Luo, and T. Wang · 2018
Earlier work this paper cites.
Boosting Self-Supervised Learning via Knowledge Transfer
M. Noroozi, A. Vinjimoor, P. Favaro, and H. Pirsiavash · 2018
Earlier work this paper cites.
With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning
B. Wang, Y. Yao, B. Viswanath, and H. Zheng · 2018
Cited alongside, same era.
Low-Shot Learning from Imaginary Data
Y. Wang, R. Girshick, M. Hebert, and B. Hariharan · 2018
Cited alongside, same era.
Amazon Rekognition
Amazon · 2019
Cited alongside, same era.
Image Block Augmentation for One-Shot Learning
Z. Chen, Y. Fu, K. Chen, and Y. Jiang · 2019
Cited alongside, same era.
Multi-Level Semantic Feature Augmentation for One-Shot Learning
Z. Chen, Y. Fu, Y. Zhang, Y. Jiang, X. Xue, and L. Sigal · 2019
Cited alongside, same era.
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
A. Salem, Y. Zhang, M. Humbert, M. Fritz, and M. Backes · 2019
Cited alongside, same era.
Generalizing from a Few Examples: A Survey on Few-shot Learning
Y. Wang, Q. Yao, J. T. Kwok, and L. M. Ni · 2020
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The Secret Revealer: Generative Model-Inversion Attacks against Deep Neural Networks
Y. Zhang, R. Jia, H. Pei, W. Wang, B. Li, and D. Song · 2020
Later among the works it cites.
The Secret Revealer: Generative Model-Inversion Attacks against Deep Neural Networks
Y. Zhang, R. Jia, H. Pei, W. Wang, B. Li, and D. Song · 2020
Later among the works it cites.
Y. Zou, Z. Zhang, M. Backes, and Y. Zhang · 2020
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Certifiably Robust Variational Autoencoders
B. Barrett, A. Camuto, M. Willetts, and T. Rainforth · 2021
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A Survey on Image Data Augmentation for Deep Learning
C. Shorten and T. M. Khoshgoftaar · 2019
Cited alongside, same era.
A Survey of Zero-Shot Learning: Settings, Methods, and Applications
W. Wang, V. W. Zheng, H. Yu, and C. Miao · 2019
Cited alongside, same era.
Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment
Z. Yang, J. Zhang, E. Chang, and Z. Liang · 2019
Cited alongside, same era.
Latent Backdoor Attacks on Deep Neural Networks
Y. Yao, H. Li, H. Zheng, and B. Y. Zhao · 2019
Cited alongside, same era.
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
S. Yun, D. Han, S. J. Oh, S. Chun, J. Choe, and Y. Yoo · 2019
Cited alongside, same era.
Inverting Gradients - How easy is it to break privacy in federated learning?
J. Geiping, H. Bauermeister, H. Droge, and M. Moeller · 2020
Cited alongside, same era.
J. Breier, D. Jap, X. Hou, S. Bhasin, and Y. Liu · 2021
Later among the works it cites.
Extracting Training Data from Large Language Models
N. Carlini, F. Tramer, E. Wallace, M. Jagielski, A. Herbert-Voss, K. Lee, A. Roberts, T. Brown, D. Song, U. Erlingsson, A. Oprea, and C. Raffel · 2021
Later among the works it cites.
Knowledge-aware Zero-Shot Learning: Survey and Perspective
J. Chen, Y. Geng, Z. Chen, I. Horrocks, J. Z. Pan, and H. Chen · 2021
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Regularisation of neural networks by enforcing Lipschitz continuity
H. Gouk1, E. Frank, B. Pfahringer, and M. J. Cree · 2021
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TransMIA: Membership Inference Attacks Using Transfer Shadow Training
S. Hidano, T. Murakami, and Y. Kawamoto · 2021
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Self-Supervised Visual Feature Learning with Deep Neural Networks: A Survey
L. Jing and Y. Tian · 2021
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Self-supervised Learning: Generative or Contrastive
X. Liu, F. Zhang, Z. Hou, L. Mian, Z. Wang, J. Zhang, and J. Tang · 2021
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Negative Data Augmentation
A. Sinha, K. Ayush, J. Song, B. Uzkent, H. Jin, and S. Ermon · 2021
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See through Gradients: Image Batch Recovery via GradInversion)
H. Yin, A. Mallya, A. Vahdat, J. M. Alvarez, J. Kautz, and P. Molehanov · 2021
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Exploiting Explanations for Model Inversion Attacks
X. Zhao, W. Zhang, X. Xiao, and B. Lim · 2021
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A Comprehensive Survey on Transfer Learning
F. Zhuang, Z. Qi, K. Duan, D. Xi, and Y. Zhu · 2021
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