Следене
Min Lin
Min Lin
Principal Research Scientist, Sea AI Lab
Потвърден имейл адрес: sea.com - Начална страница
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Позовавания
Позовавания
Година
Network In Network
M Lin, Q Chen, S Yan
International Conference on Learning Representations, 2013
99152013
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ...
29052015
On the spectral bias of neural networks
N Rahaman, A Baratin, D Arpit, F Draxler, M Lin, F Hamprecht, Y Bengio, ...
International conference on machine learning, 5301-5310, 2019
15132019
Gradient based sample selection for online continual learning
R Aljundi, M Lin, B Goujaud, Y Bengio
Advances in neural information processing systems 32, 2019
9582019
HCP: A Flexible CNN Framework for Multi-label Image Classification
Y Wei, W Xia, M Lin, J Huang, B Ni, J Dong, Y Zhao, S Yan
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
7112015
Online continual learning with maximal interfered retrieval
R Aljundi, E Belilovsky, T Tuytelaars, L Charlin, M Caccia, M Lin, ...
Advances in neural information processing systems 32, 2019
6072019
NUS-PRO: A New Visual Tracking Challenge
A Li, M Lin, Y Wu, MH Yang, S Yan
IEEE transactions on pattern analysis and machine intelligence 38, 335--349, 2016
2212016
Better diffusion models further improve adversarial training
Z Wang, T Pang, C Du, M Lin, W Liu, S Yan
International Conference on Machine Learning, 36246-36263, 2023
2092023
Online fast adaptation and knowledge accumulation (osaka): a new approach to continual learning
M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, ...
Advances in Neural Information Processing Systems 33, 16532-16545, 2020
159*2020
On evaluating adversarial robustness of large vision-language models
Y Zhao, T Pang, C Du, X Yang, C Li, NMM Cheung, M Lin
Advances in Neural Information Processing Systems 36, 2024
1552024
Causal attention for interpretable and generalizable graph classification
Y Sui, X Wang, J Wu, M Lin, X He, TS Chua
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
1552022
Robustness and accuracy could be reconcilable by (proper) definition
T Pang, M Lin, X Yang, J Zhu, S Yan
International Conference on Machine Learning, 17258-17277, 2022
1412022
Lorahub: Efficient cross-task generalization via dynamic lora composition
C Huang, Q Liu, BY Lin, T Pang, C Du, M Lin
arXiv preprint arXiv:2307.13269, 2023
1272023
A recipe for watermarking diffusion models
Y Zhao, T Pang, C Du, X Yang, NM Cheung, M Lin
arXiv preprint arXiv:2303.10137, 2023
1142023
Correntropy induced l2 graph for robust subspace clustering
C Lu, J Tang, M Lin, L Lin, S Yan, Z Lin
Proceedings of the IEEE International Conference on Computer Vision, 1801--1808, 2013
1042013
Causal representation learning for out-of-distribution recommendation
W Wang, X Lin, F Feng, X He, M Lin, TS Chua
Proceedings of the ACM Web Conference 2022, 3562-3571, 2022
1002022
How should pre-trained language models be fine-tuned towards adversarial robustness?
X Dong, AT Luu, M Lin, S Yan, H Zhang
Advances in Neural Information Processing Systems 34, 4356-4369, 2021
582021
Envpool: A highly parallel reinforcement learning environment execution engine
J Weng, M Lin, S Huang, B Liu, D Makoviichuk, V Makoviychuk, Z Liu, ...
Advances in Neural Information Processing Systems 35, 22409-22421, 2022
522022
Programming a Pavlovian-like conditioning circuit in Escherichia coli
H Zhang, M Lin, H Shi, W Ji, L Huang, X Zhang, S Shen, R Gao, S Wu, ...
Nature communications 5 (1), 3102, 2014
522014
Bag of tricks for training data extraction from language models
W Yu, T Pang, Q Liu, C Du, B Kang, Y Huang, M Lin, S Yan
International Conference on Machine Learning, 40306-40320, 2023
412023
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