Hao Wang

Orcid: 0000-0002-6949-7241

Affiliations:

Harvard University, Cambridge, MA, USA

According to our database¹, Hao Wang authored at least 18 papers between 2017 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Article

PhD thesis

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Bibliography

2023

Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels.

[BibT_eX]

[DOI]

Hao Wang

Rui Gao

Flávio P. Calmon

J. Mach. Learn. Res., 2023

Adapting Fairness Interventions to Missing Values.

[BibT_eX]

[DOI]

Raymond Feng

Flávio P. Calmon

Hao Wang

CoRR, 2023

Aleatoric and Epistemic Discrimination in Classification.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction.

[BibT_eX]

[DOI]

CoRR, 2022

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values.

[BibT_eX]

[DOI]

Haewon Jeong

Hao Wang

Flávio P. Calmon

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

To Split or not to Split: The Impact of Disparate Treatment in Classification.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2021

Learning While Dissipating Information: Understanding the Generalization Capability of SGLD.

[BibT_eX]

[DOI]

CoRR, 2021

Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Impact of Split Classifiers on Group Fairness.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

2020

On the Robustness of Information-Theoretic Privacy Measures and Mechanisms.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2020

Model Projection: Theory and Applications to Fair Machine Learning.

[BibT_eX]

[DOI]

Karthikeyan Natesan Ramamurthy

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Privacy With Estimation Guarantees.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2019

An Information-Theoretic View of Generalization via Wasserstein Distance.

[BibT_eX]

[DOI]

Hao Wang

Mario Díaz

José Cândido Silveira Santos Filho

Flávio P. Calmon

Proceedings of the IEEE International Symposium on Information Theory, 2019

Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions.

[BibT_eX]

[DOI]

Hao Wang

Berk Ustun

Flávio P. Calmon

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning.

[BibT_eX]

[DOI]

Hao Wang

Berk Ustun

Flávio P. Calmon

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

The Utility Cost of Robust Privacy Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

An estimation-theoretic view of privacy.

[BibT_eX]

[DOI]

Hao Wang

Flávio P. Calmon

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Hao Wang

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