6 citations · 10 across the 3 of their papers we have counts for
6 papers
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…
The layer number of -evenly distributed point sets
Ilkyoo Choi, Weonyoung Joo, Minki Kim
For a finite point set in , we consider a peeling process where the vertices of the convex hull are removed at each step. The layer number of a given point set…
Adversarial Likelihood-Free Inference on Black-Box Generator
Dongjun Kim, Weonyoung Joo, Seungjae Shin +2
Generative Adversarial Network (GAN) can be viewed as an implicit estimator of a data distribution, and this perspective motivates using the adversarial concept in the true input p…
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…
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Mingi Ji, Weonyoung Joo, Kyungwoo Song +2
Recent studies identified that sequential Recommendation is improved by the attention mechanism. By following this development, we propose Relation-Aware Kernelized Self-Attention…
Dirichlet Variational Autoencoder
Weonyoung Joo, Wonsung Lee, Sungrae Park +1
This paper proposes Dirichlet Variational Autoencoder (DirVAE) using a Dirichlet prior for a continuous latent variable that exhibits the characteristic of the categorical probabil…