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Jiaheng Wei
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引用次数
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年份
Learning with noisy labels revisited: A study using real-world human annotations
J Wei, Z Zhu, H Cheng, T Liu, G Niu, Y Liu
ICLR 2022, 2022
2152022
To smooth or not? when label smoothing meets noisy labels
J Wei, H Liu, T Liu, G Niu, M Sugiyama, Y Liu
ICML 2022 (Long Presentation), 2022
75*2022
When optimizing -divergence is robust with label noise
J Wei, Y Liu
ICLR 2021, 2021
492021
To aggregate or not? learning with separate noisy labels
J Wei, Z Zhu, T Luo, E Amid, A Kumar, Y Liu
KDD 2023, 2023
252023
Incentives for federated learning: a hypothesis elicitation approach
Y Liu, J Wei
ICML 2020 (workshop), 2020
202020
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training
J Wei, M Liu, J Luo, A Zhu, J Davis, Y Liu
ECCV 2022, 2022
19*2022
Distributionally Robust Post-hoc Classifiers under Prior Shifts
J Wei, H Narasimhan, E Amid, WS Chu, Y Liu, A Kumar
ICLR 2023, 2023
132023
Human-instruction-free llm self-alignment with limited samples
H Guo, Y Yao, W Shen, J Wei, X Zhang, Z Wang, Y Liu
arXiv preprint arXiv:2401.06785, 2024
62024
Do humans and machines have the same eyes? human-machine perceptual differences on image classification
M Liu, J Wei, Y Liu, J Davis
arXiv preprint arXiv:2304.08733, 2023
62023
Fairness improves learning from noisily labeled long-tailed data
J Wei, Z Zhu, G Niu, T Liu, S Liu, M Sugiyama, Y Liu
arXiv preprint arXiv:2303.12291, 2023
62023
Measuring and reducing llm hallucination without gold-standard answers via expertise-weighting
J Wei, Y Yao, JF Ton, H Guo, A Estornell, Y Liu
arXiv preprint arXiv:2402.10412, 2024
52024
Sample Elicitation
J Wei, Z Fu, Y Liu, X Li, Z Yang, Z Wang
AISTATS 2021, 2692-2700, 2021
42021
Auditing for Federated Learning: A Model Elicitation Approach
Y Liu, R Lou, J Wei
Proceedings of the Fifth International Conference on Distributed Artificial …, 2023
22023
Consensus on dynamic stochastic block models: Fast convergence and phase transitions
H Wang, J Wei, Z Zhang
arXiv preprint arXiv:2209.03999, 2022
12022
Harnessing Business and Media Insights with Large Language Models
Y Bao, AP Shah, N Narang, J Rivers, R Maksey, L Guan, LN Barrere, ...
arXiv preprint arXiv: 2406.06559, 2024
2024
Incentivizing Data Collection from Heterogeneous Clients in Federated Learning
J Pang, J Wei, C Qian, Y Liu
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