Yonggang ZHANG
Yonggang ZHANG
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Prompt Distribution Learning
Y Lu, J Liu, Y Zhang, Y Liu, X Tian
CVPR 2022, 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
Y Chen, Y Zhang, H Yang, K Ma, B Xie, T Liu, B Han, J Cheng
NeurIPS 2022, 2022
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Y Chen, H Yang, Y Zhang, K Ma, T Liu, B Han, J Cheng
ICLR 2022, 2022
CausalAdv: Adversarial Robustness Through the Lens of Causality
Y Zhang, M Gong, T Liu, G Niu, X Tian, B Han, B Schölkopf, K Zhang
ICLR 2022, 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
Z Tang*, Y Zhang*, S Shi, X He, B Han, X Chu
ICML 2022, 2022
Principal Component Adversarial Example
Y Zhang, X Tian, Y Li, X Wang, D Tao
TIP 2020, 2020
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
Y Chen, K Zhou, Y Bian, B Xie, K Ma, Y Zhang, H Yang, B Han, J Cheng
ICLR 2023, 2023
Class-Disentanglement and Applications in Adversarial Detection and Defense
K Yang, T Zhou, Y Zhang, X Tian, D Tao
NeurIPS 2021, 2021
Meta Convolutional Neural Networks for Single Domain Generalization
C Wan, X Shen, Y Zhang, Z Yin, X Tian, F Gao, J Huang, XS Hua
CVPR 2022, 2022
Watermarking for Out-of-distribution Detection
Q Wang, F Liu, Y Zhang, J Zhang, C Gong, T Liu, B Han
NeurIPS 2022, 2022
Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
Y Zhang, Y Li, T Liu, X Tian
ICML 2020, 2020
Moderately Distributional Exploration for Domain Generalization
R Dai, Y Zhang*, Z Fang, B Han, X Tian*
ICML 2023, 2023
Towards Lightweight Black-Box Attacks against Deep Neural Networks
C Sun, Y Zhang, W Chaoqun, Q Wang, Y Li, T Liu, B Han, X Tian
NeurIPS 2022, 2022
Hard Sample Matters a Lot in Zero-Shot Quantization
H Li*, X Wu, F Lv, D Liao, TH Li, Y Zhang*, B Han, M Tan
CVPR 2023, 2023
Learning to augment distributions for out-of-distribution detection
Q Wang, Z Fang, Y Zhang, F Liu, Y Li, B Han
NeurIPS 2023, 2023
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
Z Yang*, Y Zhang*, Y Zheng, X Tian, H Peng, T Liu, B Han
NeurIPS 2023, 2023
Continual Named Entity Recognition without Catastrophic Forgetting
D Zhang, W Cong, J Dong, Y Yu, X Chen, Y Zhang, Z Fang
EMNLP 2023, 2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
Z Tang, X Chu, RY Ran, S Lee, S Shi, Y Zhang, Y Wang, AQ Liang, ...
Preprint, 2023
Invariant Learning via Probability of Sufficient and Necessary Causes
M Yang, Z Fang, Y Zhang*, Y Du, F Liu, JF Ton, J Wang*
NeurIPS 2023 (Spotlight), 2023
Out-of-Distribution Detection with Negative Prompts
J Nie, Y Zhang, Z Fang, T Liu, B Han, X Tian
ICLR 2024, 2024
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