Publications

221 results for Adversarial Robustness and Privacy

Adversarial Attack Generation Empowered by Min-Max Optimization
- - Jingkang Wang
  - Tianyun Zhang
  - et al.
- 2021
- NeurIPS 2021
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations
- - Yu-Lin Tsai
  - Chia-Yi Hsu
  - et al.
- 2021
- NeurIPS 2021
WristPrint: Characterizing User Re-identification Risks from Wrist-worn Accelerometry Data
- - Nazir Saleheen
  - Md Azim Ullah
  - et al.
- 2021
- CCS 2021
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy
- - Linkang Du
  - Zhikun Zhang
  - et al.
- 2021
- CCS 2021
Privacy preserving explanations for hierarchical time series forecasts
- - Surya Shravan Kumar Sajja
  - Sumanta Mukherjee
  - et al.
- 2021
- INFORMS 2021
Secure Random Sampling in Differential Privacy
- - Naoise Holohan
  - Stefano Braghin
- 2021
- ESORICS 2021
Anonymizing Machine Learning Models
- - Abigail Goldsteen
  - Micha Moffie
  - et al.
- 2021
- ESORICS 2021
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
- - Xiao Zang
  - Yi Xie
  - et al.
- 2021
- IJCAI 2021
Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks
- - Siyue Wang
  - Xiao Wang
  - et al.
- 2021
- IJCAI 2021
Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021)
- - Pin-Yu Chen
  - Cho-Jui Hsieh
  - et al.
- 2021
- KDD 2021