Veit, Andreas

How to backdoor federated learning

Bagdasaryan, E., Veit, A., Hua, Y., Estrin, D., & Shmatikov, V. (2018) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 1,495

Residual Networks Behave Like Ensembles of Relatively Shallow Networks

Veit, A., Wilber, M., & Belongie, S. (2016) · arXiv

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 705

Understanding Robustness of Transformers for Image Classification

Bhojanapalli, S., Chakrabarti, A., Glasner, D., Li, D., Unterthiner, T., & Veit, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 440

Deep Learning is Robust to Massive Label Noise

Rolnick, D., Veit, A., Belongie, S., & Shavit, N. (2017) · arXiv

Machine Learning and Data ClassificationDomain Adaptation and Few-Shot Learning

Cited by 402

Large Language Models with Controllable Working Memory

Li, D., Rawat, A. S., Zaheer, M., Wang, X., Lukasik, M., Veit, A., Yu, F., & Kumar, S. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingNatural Language Processing Techniques

Cited by 46