Adversarial Examples in Modern Machine Learning: A Review
Authors: Rey Reza Wiyatno, Anqi Xu, Ousmane Dia, Archy de Berker | Published: 2019-11-13 | Updated: 2019-11-15
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks
Authors: Aditya Golatkar, Alessandro Achille, Stefano Soatto | Published: 2019-11-12 | Updated: 2020-03-31
On Robustness to Adversarial Examples and Polynomial Optimization
Authors: Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan | Published: 2019-11-12
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory
Authors: Arash Rahnama, Andre T. Nguyen, Edward Raff | Published: 2019-11-12
RAD: On-line Anomaly Detection for Highly Unreliable Data
Authors: Zilong Zhao, Robert Birke, Rui Han, Bogdan Robu, Sara Bouchenak, Sonia Ben Mokhtar, Lydia Y. Chen | Published: 2019-11-11
DRAB-LOCUS: An Area-Efficient AES Architecture for Hardware Accelerator Co-Location on FPGAs
Authors: Jacob T. Grycel, Robert J. Walls | Published: 2019-11-11
Privacy-Preserving Gradient Boosting Decision Trees
Authors: Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He | Published: 2019-11-11 | Updated: 2022-10-10
Collaborative Homomorphic Computation on Data Encrypted under Multiple Keys
Authors: Asma Aloufi, Peizhao Hu | Published: 2019-11-11
Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy
Authors: Xinghua Qu, Zhu Sun, Yew-Soon Ong, Abhishek Gupta, Pengfei Wei | Published: 2019-11-10 | Updated: 2020-10-29
Preservation of Anomalous Subgroups On Machine Learning Transformed Data
Authors: Samuel C. Maina, Reginald E. Bryant, William O. Goal, Robert-Florian Samoilescu, Kush R. Varshney, Komminist Weldemariam | Published: 2019-11-09