Comment on “Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network”
Authors: Roland S. Zimmermann | Published: 2019-07-01
深層学習手法
Adversarial Robustness via Label-Smoothing
Authors: Morgane Goibert, Elvis Dohmatob | Published: 2019-06-27 | Updated: 2019-10-15
Adversarial Examples to Fool Iris Recognition Systems
Authors: Sobhan Soleymani, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi | Published: 2019-06-21 | Updated: 2019-07-18
Convergence of Adversarial Training in Overparametrized Neural Networks
Authors: Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee | Published: 2019-06-19 | Updated: 2019-11-09
Real or Fake? Learning to Discriminate Machine from Human Generated Text
Authors: Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc'Aurelio Ranzato, Arthur Szlam | Published: 2019-06-07 | Updated: 2019-11-25
Can You Trust Your Model’s Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Authors: Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek | Published: 2019-06-06 | Updated: 2019-12-17
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
Authors: Paweł Morawiecki, Przemysław Spurek, Marek Śmieja, Jacek Tabor | Published: 2019-06-03 | Updated: 2019-07-03
IoT Network Security from the Perspective of Adversarial Deep Learning
Authors: Yalin E. Sagduyu, Yi Shi, Tugba Erpek | Published: 2019-05-31
Unlabeled Data Improves Adversarial Robustness
Authors: Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang, John C. Duchi | Published: 2019-05-31 | Updated: 2022-01-13
L0 Regularization Based Neural Network Design and Compression
Authors: S. Asim Ahmed | Published: 2019-05-31