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Yifei Wang
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Year
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap
Y Wang*, Q Zhang*, Y Wang, J Yang, Z Lin
ICLR 2022, 2022
1012022
Dissecting the diffusion process in linear graph convolutional networks
Y Wang, Y Wang, J Yang, Z Lin
NeurIPS 2021, 2021
632021
Jailbreak and guard aligned language models with only few in-context demonstrations
Z Wei, Y Wang, Y Wang
arXiv preprint arXiv:2310.06387, 2023
462023
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders
Q Zhang*, Y Wang*, Y Wang
NeurIPS 2022 Spotlight, 2022
332022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Y Mo, D Wu, Y Wang, Y Guo, Y Wang
NeurIPS 2022 Spotlight, 2022
302022
Residual relaxation for multi-view representation learning
Y Wang, Z Geng, F Jiang, C Li, Y Wang, J Yang, Z Lin
NeurIPS 2021, 2021
302021
Optimization-induced graph implicit nonlinear diffusion
Q Chen, Y Wang, Y Wang, J Yang, Z Lin
ICML 2022, 2022
292022
CFA: Class-wise Calibrated Fair Adversarial Training
Z Wei, Y Wang, Y Guo, Y Wang
CVPR 2023, 2023
262023
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond
X Guo*, Y Wang*, T Du*, Y Wang
ICLR 2023, 2023
232023
G CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters
M Li, X Guo, Y Wang, Y Wang, Z Lin
ICML 2022, 2022
192022
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Z Zhuo*, Y Wang*, J Ma, Y Wang
ICLR 2023, 2023
152023
A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Y Wang*, Q Zhang*, T Du, J Yang, Z Lin, Y Wang
ICLR 2023, 2023
102023
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning
R Luo*, Y Wang*, Y Wang
ICLR 2023, 2023
92023
Fooling Adversarial Training with Inducing Noise
Z Wang*, Y Wang*, Y Wang
arXiv preprint arXiv:2111.10130, 2021
92021
Rethinking Weak Supervision in Helping Contrastive Learning
J Cui*, W Huang*, Y Wang*, Y Wang
ICML 2023, 2023
82023
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors
Q Wang*, Y Wang*, H Zhu, Y Wang
NeurIPS 2022 Spotlight, 2022
82022
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training
Y Wang, Y Wang, J Yang, Z Lin
ICLR 2022, 2022
82022
Train once, and decode as you like
C Tian, Y Wang, H Cheng, Y Lian, Z Zhang
COLING 2020, 2020
72020
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Y Wang*, L Li*, J Yang, Z Lin, Y Wang
NeurIPS 2023, 2023
62023
On the Generalization of Multi-modal Contrastive Learning
Q Zhang*, Y Wang*, Y Wang
ICML 2023, 2023
52023
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