Results 231 to 240 of about 27,717 (260)

Individualized Treatment Effect Inference of Head and Neck Cancer with Multimodal Data. [PDF]

open access: yesAPSIPA Trans Signal Inf Process
Wei Y   +5 more
europepmc   +1 more source

Transfer learning for T-cell response prediction. [PDF]

open access: yesBMC Bioinformatics
Stadelmaier J, Malone B, Eggeling R.
europepmc   +1 more source

Large reasoning models are autonomous jailbreak agents. [PDF]

open access: yesNat Commun
Hagendorff T, Derner E, Oliver N.
europepmc   +1 more source

Learning Universal Adversarial Perturbation by Adversarial Example

Proceedings of the AAAI Conference on Artificial Intelligence, 2022
Deep learning models have shown to be susceptible to universal adversarial perturbation (UAP), which has aroused wide concerns in the community. Compared with the conventional adversarial attacks that generate adversarial samples at the instance level, UAP can fool the target model for different instances with only a single perturbation, enabling us to
Maosen Li   +4 more
openaire   +1 more source

On The Generation of Unrestricted Adversarial Examples

2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), 2020
Adversarial examples are inputs designed by an adversary with the goal of fooling the machine learning models. Most of the research about adversarial examples have focused on perturbing the natural inputs with the assumption that the true label remains unchanged.
Mehrgan Khoshpasand   +1 more
openaire   +1 more source

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