Fetching the paper…
Reading the bibliography…
Machine unlearning aims to revoke some training data after learning in response to requests from users, model developers, and administrators.
LOGAN: Local Group Bias Detection by Clustering
Zhao, J.; and Chang, K. 2020 · 1977
Earlier work this paper cites.
Catastrophic Interference in Connectionist Networks: Can It Be Predicted, Can It Be Prevented?
French, R. M. 1993 · 1993
Earlier work this paper cites.
Visualizing higher-layer features of a deep network
Erhan, D.; Bengio, Y.; Courville, A.; and Vincent, P. 2009 · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, A.; Hinton, G.; et al. 2009 · 2009
Earlier work this paper cites.
The Algorithmic Foundations of Differential Privacy
Dwork, C.; and Roth, A. 2014 · 2014
Earlier work this paper cites.
Towards Making Systems Forget with Machine Unlearning
Cao, Y.; and Yang, J. 2015 · 2015
Earlier work this paper cites.
Tiny imagenet visual recognition challenge
Le, Y.; and Yang, X. 2015 · 2015
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K.; and Zisserman, A. 2015 · 2015
Earlier work this paper cites.
Going deeper with convolutions
Szegedy, C.; Liu, W.; Jia, Y.; Sermanet, P.; Reed, S. E.; Anguelov, D.; Erhan, D.; Vanhoucke, V.; and Rabinovich, A. 2015 · 2015
Earlier work this paper cites.
Closed-form Estimators for High-dimensional Generalized Linear Models
Yang, E.; Lozano, A. C.; and Ravikumar, P. K. 2015 · 2015
Earlier work this paper cites.
Deep Learning with Differential Privacy
Abadi, M.; Chu, A.; Goodfellow, I. J.; McMahan, H. B.; Mironov, I.; Talwar, K.; and Zhang, L. 2016 · 2016
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Earlier work this paper cites.
Approximate Data Deletion from Machine Learning Models
Izzo, Z.; Smart, M. A.; Chaudhuri, K.; and Zou, J. 2021 · 2016
Earlier work this paper cites.
Second-Order Stochastic Optimization for Machine Learning in Linear Time
Agarwal, N.; Bullins, B.; and Hazan, E. 2017 · 2017
Earlier work this paper cites.
Densely Connected Convolutional Networks
Huang, G.; Liu, Z.; van der Maaten, L.; and Weinberger, K. Q. 2017 · 2017
Cited alongside, same era.
Overcoming catastrophic forgetting in neural networks
Kirkpatrick, J.; Pascanu, R.; Rabinowitz, N.; Veness, J.; Desjardins, G.; Rusu, A. A.; Milan, K.; Quan, J.; Ramalho, T.; Grabska-Barwinska, A.; et al. 2017 · 2017
Cited alongside, same era.
Understanding Black-box Predictions via Influence Functions
Koh, P. W.; and Liang, P. 2017 · 2017
Cited alongside, same era.
Finding label noise examples in large scale datasets
Rajmadhan, E.; Goldgof, D. B.; and Hall, L. O. 2017 · 2017
Cited alongside, same era.
Memory Aware Synapses: Learning What (not) to Forget
Aljundi, R.; Babiloni, F.; Elhoseiny, M.; Rohrbach, M.; and Tuytelaars, T. 2018 · 2018
Cited alongside, same era.
Efficient Lifelong Learning with A-GEM
Chaudhry, A.; Ranzato, M.; Rohrbach, M.; and Elhoseiny, M. 2019 · 2019
Machine Unlearning for Random Forests
Brophy, J.; and Lowd, D. 2021 · 2021
Later among the works it cites.
Mitigating backdoor attacks in LSTM-based text classification systems by Backdoor Keyword Identification
Chen, C.; and Dai, J. 2021 · 2021
Later among the works it cites.
Dynamic Differential-Privacy Preserving SGD
Du, J.; Li, S.; Mo, F.; and Chen, S. 2021 · 2021
Later among the works it cites.
Network Pruning That Matters: A Case Study on Retraining Variants
Le, D. H.; and Hua, B. 2021 · 2021
Later among the works it cites.
Generalized Variational Continual Learning
Loo, N.; Swaroop, S.; and Turner, R. E. 2021 · 2021
Later among the works it cites.
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Making AI Forget You: Data Deletion in Machine Learning
Ginart, A.; Guan, M. Y.; Valiant, G.; and Zou, J. 2019 · 2019
Cited alongside, same era.
Memory Efficient Experience Replay for Streaming Learning
Hayes, T. L.; Cahill, N. D.; and Kanan, C. 2019 · 2019
Cited alongside, same era.
Learning Not to Learn: Training Deep Neural Networks With Biased Data
Kim, B.; Kim, H.; Kim, K.; Kim, S.; and Kim, J. 2019 · 2019
Cited alongside, same era.
On the Accuracy of Influence Functions for Measuring Group Effects
Koh, P. W.; Ang, K.; Teo, H. H. K.; and Liang, P. 2019 · 2019
Cited alongside, same era.
Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
Li, X.; Zhou, Y.; Wu, T.; Socher, R.; and Xiong, C. 2019 · 2019
Cited alongside, same era.
Understanding the role of individual units in a deep neural network
Bau, D.; Zhu, J.; Strobelt, H.; Lapedriza, À.; Zhou, B.; and Torralba, A. 2020 · 2020
Cited alongside, same era.
Ma, X.; Yuan, G.; Shen, X.; Chen, T.; Chen, X.; Chen, X.; Liu, N.; Qin, M.; Liu, S.; Wang, Z.; and Wang, Y. 2021 · 2021
Later among the works it cites.
Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger
Qi, F.; Li, M.; Chen, Y.; Zhang, Z.; Liu, Z.; Wang, Y.; and Sun, M. 2021 · 2021
Later among the works it cites.
Adaptive Consistency Prior Based Deep Network for Image Denoising
Ren, C.; He, X.; Wang, C.; and Zhao, Z. 2021 · 2021
Later among the works it cites.
InsideBias: Measuring Bias in Deep Networks and Application to Face Gender Biometrics
Serna, I.; Peña, A.; Morales, A.; and Fiérrez, J. 2020 · 2021
Later among the works it cites.
Learning with Selective Forgetting
Shibata, T.; Irie, G.; Ikami, D.; and Mitsuzumi, Y. 2021 · 2021
Later among the works it cites.
DeHiB: Deep Hidden Backdoor Attack on Semi-supervised Learning via Adversarial Perturbation
Yan, Z.; Li, G.; TIan, Y.; Wu, J.; Li, S.; Chen, M.; and Poor, H. V. 2021 · 2021
Later among the works it cites.
Federated Unlearning via Class-Discriminative Pruning
Wang, J.; Guo, S.; Xie, X.; and Qi, H. 2022 · 2022
Later among the works it cites.
Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising
Pang, T.; Zheng, H.; Quan, Y.; and Ji, H. 2021 · 2052
Closest in time.