Junyi Zhu
Junyi Zhu
Department of Electrical Engineering, KU Levuen
Verified email at - Homepage
Cited by
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R-GAP: Recursive Gradient Attack on Privacy
J Zhu, M Blaschko
International Conference on Learning Representations (ICLR), 2020
Learning path tracking for real car-like mobile robots from simulation
D Kamran, J Zhu, M Lauer
2019 European Conference on Mobile Robots (ECMR), 1-6, 2019
Confidence-aware personalized federated learning via variational expectation maximization
J Zhu, X Ma, MB Blaschko
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern†…, 2023
Improving Differentially Private SGD via Randomly Sparsified Gradients
J Zhu, MB Blaschko
Transactions on Machine Learning Research, 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
J Zhu, R Yao, MB Blaschko
International Conference on Machine Learning (ICML), 2023
Localization in Aerial Imagery with Grid Maps using LocGAN
H Hu, J Zhu, S Wirges, M Lauer
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2860-2865, 2019
Tackling Personalized Federated Learning with Label Concept Drift via Hierarchical Bayesian Modeling
X Ma, J Zhu, MB Blaschko
Workshop on Federated Learning: Recent Advances and New Challenges (in†…, 0
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
E Liu, J Zhu, Z Lin, X Ning, MB Blaschko, S Yekhanin, S Yan, G Dai, ...
arXiv preprint arXiv:2404.02241, 2024
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
E Liu, J Zhu, Z Lin, X Ning, MB Blaschko, S Yan, G Dai, H Yang, Y Wang
arXiv preprint arXiv:2407.00945, 2024
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models
J Zhu, S Liu, Y Yu, B Tang, Y Yan, Z Li, F Xiong, T Xu, MB Blaschko
arXiv preprint arXiv:2406.16069, 2024
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction
J Shi, J Zhu, DM Pelt, KJ Batenburg, MB Blaschko
arXiv preprint arXiv:2405.02509, 2024
Rescaling intermediate features makes trained consistency models perform better
J Zhu, Z Lin, E Liu, X Ning, M Blaschko
The Second Tiny Papers Track at ICLR 2024, 2024
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