Samuel Yeom

According to our database, Samuel Yeom authored at least 12 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Black-Box Audits for Group Distribution Shifts.

Marc Juarez, Samuel Yeom, Matt Fredrikson

CoRR, 2022

2021

Black-Box Approaches to Fair Machine Learning.

Samuel Yeom

PhD thesis, 2021

Avoiding Disparity Amplification under Different Worldviews.

Samuel Yeom, Michael Carl Tschantz

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning.

Samuel Yeom, Irene Giacomelli, Alan Menaged, Matt Fredrikson, Somesh Jha

J. Comput. Secur., 2020

Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness.

Samuel Yeom, Matt Fredrikson

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

FlipTest: fairness testing via optimal transport.

Emily Black, Samuel Yeom, Matt Fredrikson

Proceedings of the FAT* '20: Conference on Fairness, 2020

Learning Fair Representations for Kernel Models.

Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

FlipTest: Fairness Auditing via Optimal Transport.

Emily Black, Samuel Yeom, Matt Fredrikson

CoRR, 2019

2018

Discriminative but Not Discriminatory: A Comparison of Fairness Definitions under Different Worldviews.

Samuel Yeom, Michael Carl Tschantz

CoRR, 2018

Hunting for Discriminatory Proxies in Linear Regression Models.

Samuel Yeom, Anupam Datta, Matt Fredrikson

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting.

Samuel Yeom, Irene Giacomelli, Matt Fredrikson, Somesh Jha

Proceedings of the 31st IEEE Computer Security Foundations Symposium, 2018

2017

The Unintended Consequences of Overfitting: Training Data Inference Attacks.

Samuel Yeom, Matt Fredrikson, Somesh Jha

CoRR, 2017