Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
Authors: Nicolas Papernot, Patrick McDaniel, Ian Goodfellow | Published: 2016-05-24
A First Look at Ad-block Detection: A New Arms Race on the Web
Authors: Muhammad Haris Mughees, Zhiyun Qian, Zubair Shafiq, Karishma Dash, Pan Hui | Published: 2016-05-19
On-Average KL-Privacy and its equivalence to Generalization for Max-Entropy Mechanisms
Authors: Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg | Published: 2016-05-08
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Authors: Nicolas Papernot, Patrick McDaniel, Ananthram Swami, Richard Harang | Published: 2016-04-28
Finding Common Characteristics Among NBA Playoff and Championship Teams: A Machine Learning Approach
Authors: Ikjyot Singh Kohli | Published: 2016-04-18 | Updated: 2017-04-03
A General Retraining Framework for Scalable Adversarial Classification
Authors: Bo Li, Yevgeniy Vorobeychik, Xinyun Chen | Published: 2016-04-09 | Updated: 2016-11-26
Towards Seamless Tracking-Free Web: Improved Detection of Trackers via One-class Learning
Authors: Muhammad Ikram, Hassan Jameel Asghar, Mohamed Ali Kaafar, Balachander Krishnamurthy, Anirban Mahanti | Published: 2016-03-20
A Survey of Stealth Malware: Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions
Authors: Ethan M. Rudd, Andras Rozsa, Manuel Günther, Terrance E. Boult | Published: 2016-03-19 | Updated: 2016-12-02
Communication-Efficient Learning of Deep Networks from Decentralized Data
Authors: H. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas | Published: 2016-02-17 | Updated: 2023-01-26
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
Authors: Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin | Published: 2016-02-16 | Updated: 2016-08-09