Samuel Yeom

Publication Activity (10 Years)

Years Active: 2017-2022
Publications (10 Years): 14

Top Topics

Trinocular Stereo

Machine Learning

Avoid Overfitting

Top Venues

Publications

Marc Juárez, Samuel Yeom, Matt Fredrikson
Black-Box Audits for Group Distribution Shifts. CoRR (2022)
Samuel Yeom, Michael Carl Tschantz
Avoiding Disparity Amplification under Different Worldviews. FAccT (2021)
Samuel Yeom, Matt Fredrikson
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness. CoRR (2020)
Samuel Yeom, Irene Giacomelli, Alan Menaged, Matt Fredrikson, Somesh Jha
Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning. J. Comput. Secur. 28 (1) (2020)
Samuel Yeom, Matt Fredrikson
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness. IJCAI (2020)
Emily Black, Samuel Yeom, Matt Fredrikson
FlipTest: fairness testing via optimal transport. FAT* (2020)
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
Learning Fair Representations for Kernel Models. AISTATS (2020)
Emily Black, Samuel Yeom, Matt Fredrikson
FlipTest: Fairness Auditing via Optimal Transport. CoRR (2019)
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
Learning Fair Representations for Kernel Models. CoRR (2019)
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, Somesh Jha
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting. CSF (2018)
Samuel Yeom, Anupam Datta, Matt Fredrikson
Hunting for Discriminatory Proxies in Linear Regression Models. CoRR (2018)
Samuel Yeom, Michael Carl Tschantz
Discriminative but Not Discriminatory: A Comparison of Fairness Definitions under Different Worldviews. CoRR (2018)
Samuel Yeom, Anupam Datta, Matt Fredrikson
Hunting for Discriminatory Proxies in Linear Regression Models. NeurIPS (2018)
Samuel Yeom, Matt Fredrikson, Somesh Jha
The Unintended Consequences of Overfitting: Training Data Inference Attacks. CoRR (2017)