7 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.CY2026
Learning Fair Demand Models
Adam N. Elmachtoub, Hyemi Kim, Jonathan Y. Tan
Data-driven pricing is increasingly prevalent in sectors such as airlines, lending, insurance, and retail. By learning demand models from customer features and setting prices accor…
cs.LG2020★ 3 cited
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
Hyemi Kim, Seungjae Shin, JoonHo Jang +4
The problem of fair classification can be mollified if we develop a method to remove the embedded sensitive information from the classification features. This line of separating th…
cs.CL2020★ 7 cited
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation
Seungjae Shin, Kyungwoo Song, JoonHo Jang +3
Recent research demonstrates that word embeddings, trained on the human-generated corpus, have strong gender biases in embedding spaces, and these biases can result in the discrimi…