"deep neural networks" Papers
11 papers found
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo, Cheng Gong, Fei Liu et al.
CVPR 2025posterarXiv:2501.07251
Some Optimizers are More Equal: Understanding the Role of Optimizers in Group Fairness
Mojtaba Kolahdouzi, Hatice Gunes, Ali Etemad
NeurIPS 2025spotlightarXiv:2504.14882
Variational Learning Finds Flatter Solutions at the Edge of Stability
Avrajit Ghosh, Bai Cong, Rio Yokota et al.
NeurIPS 2025spotlightarXiv:2506.12903
1
citations
Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling
Mingze Wang, Zeping Min, Lei Wu
ICML 2024poster
Input Margins Can Predict Generalization Too
Coenraad Mouton, Marthinus Wilhelmus Theunissen, Marelie H Davel
AAAI 2024paperarXiv:2308.15466
5
citations
MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Jiayu Zhang et al.
AAAI 2024paperarXiv:2312.13630
14
citations
Robust Universal Adversarial Perturbations
Changming Xu, Gagandeep Singh
ICML 2024poster
SPADE: Sparsity-Guided Debugging for Deep Neural Networks
Arshia Soltani Moakhar, Eugenia Iofinova, Elias Frantar et al.
ICML 2024poster
Towards Certified Unlearning for Deep Neural Networks
Binchi Zhang, Yushun Dong, Tianhao Wang et al.
ICML 2024poster
United We Stand: Using Epoch-Wise Agreement of Ensembles to Combat Overfit
Uri Stern, Daniel Shwartz, Daphna Weinshall
AAAI 2024paperarXiv:2310.11077
Unveiling Privacy, Memorization, and Input Curvature Links
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
ICML 2024poster