Reaching Data Confidentiality and Model Accountability on the CalTrain
Authors: Zhongshu Gu, Hani Jamjoom, Dong Su, Heqing Huang, Jialong Zhang, Tengfei Ma, Dimitrios Pendarakis, Ian Molloy | Published: 2018-12-07
Literature Database
A Hybrid Approach to Privacy-Preserving Federated Learning
Authors: Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou | Published: 2018-12-07 | Updated: 2019-08-14
Deep-RBF Networks Revisited: Robust Classification with Rejection
Authors: Pourya Habib Zadeh, Reshad Hosseini, Suvrit Sra | Published: 2018-12-07
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach
Authors: Rajeev Sahay, Rehana Mahfuz, Aly El Gamal | Published: 2018-12-07
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks
Authors: Amir Moradibaad, Ramin Jalilian Mashhoud | Published: 2018-12-07 | Updated: 2018-12-13
Three Tools for Practical Differential Privacy
Authors: Koen Lennart van der Veen, Ruben Seggers, Peter Bloem, Giorgio Patrini | Published: 2018-12-07
Adversarial Attacks, Regression, and Numerical Stability Regularization
Authors: Andre T. Nguyen, Edward Raff | Published: 2018-12-07
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase
Authors: Jianfeng Chi, Emmanuel Owusu, Xuwang Yin, Tong Yu, William Chan, Patrick Tague, Yuan Tian | Published: 2018-12-07
Knockoff Nets: Stealing Functionality of Black-Box Models
Authors: Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz | Published: 2018-12-06
The Limitations of Model Uncertainty in Adversarial Settings
Authors: Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes | Published: 2018-12-06 | Updated: 2019-11-17