Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
Authors: Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski | Published: 2019-07-17 | Updated: 2019-10-03
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Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods
Authors: Arif Siddiqi | Published: 2019-07-17
Decentralized & Collaborative AI on Blockchain
Authors: Justin D. Harris, Bo Waggoner | Published: 2019-07-16
Helen: Maliciously Secure Coopetitive Learning for Linear Models
Authors: Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica | Published: 2019-07-16 | Updated: 2019-09-03
Latent Adversarial Defence with Boundary-guided Generation
Authors: Xiaowei Zhou, Ivor W. Tsang, Jie Yin | Published: 2019-07-16
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Authors: Fan Yang, Mengnan Du, Xia Hu | Published: 2019-07-16 | Updated: 2019-08-15
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
Authors: Yulong Cao, Chaowei Xiao, Benjamin Cyr, Yimeng Zhou, Won Park, Sara Rampazzi, Qi Alfred Chen, Kevin Fu, Z. Morley Mao | Published: 2019-07-16 | Updated: 2019-08-20
Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning
Authors: Bao Wang, Stanley J. Osher | Published: 2019-07-16
Recovery Guarantees for Compressible Signals with Adversarial Noise
Authors: Jasjeet Dhaliwal, Kyle Hambrook | Published: 2019-07-15 | Updated: 2019-08-07
Measuring the Transferability of Adversarial Examples
Authors: Deyan Petrov, Timothy M. Hospedales | Published: 2019-07-14