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cs.LG2025
Improving Transferability of Adversarial Examples via Bayesian Attacks
Qizhang Li, Yiwen Guo, Xiaochen Yang +2
The transferability of adversarial examples allows for the attack on unknown deep neural networks (DNNs), posing a serious threat to many applications and attracting great attentio…
cs.LG2025
Machine learning with tree tensor networks, CP rank constraints, and tensor dropout
Hao Chen, Thomas Barthel
Tensor networks developed in the context of condensed matter physics try to approximate order- tensors with a reduced number of degrees of freedom that is only polynomial in …