Differential Privacy as a Causal Property, Michael Carl Tschantz, Shayak Sen, Anupam Datta, 2017.
Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies Xi He, Ashwin Machanavajjhala, Bolin Ding, SIGMOD 2014.
Privacy Amplification by Mixing and Diffusion Mechanisms, Borja Balle, Gilles Barthe, Marco Gaboardi, Joseph Geumlek, NeuRIPS 2019.
Hypothesis Testing Interpretations and Renyi Differential Privacy, Borja Balle, Gilles Barthe, Marco Gaboardi, Justin Hsu, Tetsuya Sato, AISTATS 2020.
Fair Decision Making using Privacy-Protected Data, Satya Kuppam, Ryan Mckenna, David Pujol, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, FAT* 2020.
Certified Robustness to Adversarial Examples with Differential Privacy, Mathias Lecuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana, 2018.
Random Smoothing Might be Unable to Certify L_infinity Robustness for High-Dimensional Images, Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang, 2020.
Unlabeled Data Improves Adversarial Robustness, Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang, John C. Duchi, NeuRIPS 2019.
Adversarial examples from computational constraints, Sébastien Bubeck, Eric Price, Ilya Razenshteyn, NeuRIPS 2018.
Obliviousness Makes Poisoning Adversaries Weaker, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta, 2020.
Does Distributionally Robust Supervised Learning Give Robust Classifiers? Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama, ICML 2018.
Anchor regression: heterogeneous data meets causality, Dominik Rothenhäusler, Nicolai Meinshausen, Peter Bühlmann, Jonas Peters, 2019.
Invariant Risk Minimization, Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz, 2019.
RelatIF: Identifying Explanatory Training Examples via Relative Influence, Elnaz Barshan, Marc-Etienne Brunet, Gintare Karolina Dziugaite, AISTATS 2020.
Estimating Training Data Influence by Tracking Gradient Descent, Garima Pruthi, Frederick Liu, Mukund Sundararajan, Satyen Kale, 2020.
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV), Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory Sayres, ICML 2018.