An estimation-theoretic view of privacy. - Hao Wang 063; Flávio P. Calmon (Allerton, 2017)

The Utility Cost of Robust Privacy Guarantees. - Hao Wang 063; Mario Díaz; Flávio P. Calmon; Lalitha Sankar (ISIT, 2018)

On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. - Hao Wang 063; Berk Ustun; Flávio P. Calmon (ISIT, 2018)

Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. - Hao Wang 063; Berk Ustun; Flávio P. Calmon (ICML, 2019)

An Information-Theoretic View of Generalization via Wasserstein Distance. - Hao Wang 063; Mario Díaz; José Cândido Silveira Santos Filho; Flávio P. Calmon (ISIT, 2019)

Privacy With Estimation Guarantees. - Hao Wang 063; Lisa Vo; Flávio P. Calmon; Muriel Médard; Ken R. Duffy; Mayank Varia (IEEE Trans. Inf. Theory, 2019)

Model Projection: Theory and Applications to Fair Machine Learning. - Wael Alghamdi; Shahab Asoodeh; Hao Wang 063; Flávio P. Calmon; Dennis Wei; Karthikeyan Natesan Ramamurthy (ISIT, 2020)

On the Robustness of Information-Theoretic Privacy Measures and Mechanisms. - Mario Díaz; Hao Wang 063; Flávio P. Calmon; Lalitha Sankar (IEEE Trans. Inf. Theory, 2020)

The Impact of Split Classifiers on Group Fairness. - Hao Wang 063; Hsiang Hsu; Mario Díaz; Flávio P. Calmon (ISIT, 2021)

Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels. - Hao Wang 063; Yizhe Huang; Rui Gao 001; Flávio P. Calmon (NeurIPS, 2021)

Learning While Dissipating Information: Understanding the Generalization Capability of SGLD. - Hao Wang 063; Yizhe Huang; Rui Gao 001; Flávio P. Calmon (CoRR, 2021)

To Split or not to Split: The Impact of Disparate Treatment in Classification. - Hao Wang 063; Hsiang Hsu; Mario Díaz; Flávio P. Calmon (IEEE Trans. Inf. Theory, 2021)

Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values. - Haewon Jeong; Hao Wang 063; Flávio P. Calmon (AAAI, 2022)

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection. - Wael Alghamdi; Hsiang Hsu; Haewon Jeong; Hao Wang 063; Peter Michalák; Shahab Asoodeh; Flávio P. Calmon (NeurIPS, 2022)

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction. - Wael Alghamdi; Hsiang Hsu; Haewon Jeong; Hao Wang 063; P. Winston Michalak; Shahab Asoodeh; Flávio P. Calmon (CoRR, 2022)

Adapting Fairness Interventions to Missing Values. - Raymond Feng; Flávio P. Calmon; Hao Wang 063 (NeurIPS, 2023)

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions. - Hao Wang 063; Luxi He; Rui Gao 001; Flávio P. Calmon (NeurIPS, 2023)

Aleatoric and Epistemic Discrimination in Classification. - Hao Wang 063; Luxi He; Rui Gao 001; Flávio P. Calmon (CoRR, 2023)

Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels. - Hao Wang 063; Rui Gao 001; Flávio P. Calmon (J. Mach. Learn. Res., 2023)

Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. - Ivoline C. Ngong; Swanand Ravindra Kadhe; Hao Wang 063; Keerthiram Murugesan; Justin D. Weisz; Amit Dhurandhar; Karthikeyan Natesan Ramamurthy (ACL (Findings), 2025)