Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
Authors: Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara, Masanori Yamada, Shuichi Adachi | Published: 2019-09-19
敵対的攻撃
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Authors: Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain | Published: 2019-09-17 | Updated: 2019-10-09
Exploring the Robustness of NMT Systems to Nonsensical Inputs
Authors: Akshay Chaturvedi, Abijith KP, Utpal Garain | Published: 2019-08-03 | Updated: 2020-02-28
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
Stateful Detection of Black-Box Adversarial Attacks
Authors: Steven Chen, Nicholas Carlini, David Wagner | Published: 2019-07-12
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Authors: Yulong Cao, Chaowei Xiao, Dawei Yang, Jing Fang, Ruigang Yang, Mingyan Liu, Bo Li | Published: 2019-07-11
Why Blocking Targeted Adversarial Perturbations Impairs the Ability to Learn
Authors: Ziv Katzir, Yuval Elovici | Published: 2019-07-11
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
Authors: Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison Cottrell, Geoffrey Hinton | Published: 2019-07-05 | Updated: 2020-02-18