Suh, Changho

16 publications

AAAI 2023 A Fair Generative Model Using LeCam Divergence Soobin Um, Changho Suh

ICML 2023 Improving Fair Training Under Correlation Shifts Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh

ICLR 2021 FairBatch: Batch Selection for Model Fairness Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh

NeurIPS 2021 Sample Selection for Fair and Robust Training Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh

NeurIPS 2020 A Fair Classifier Using Kernel Density Estimation Jaewoong Cho, Gyeongjo Hwang, Changho Suh

ECCV 2020 Autoencoder-Based Graph Construction for Semi-Supervised Learning Mingeun Kang, Kiwon Lee, Yong H. Lee, Changho Suh

ICML 2020 FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh

NeurIPS 2020 Matrix Completion with Hierarchical Graph Side Information Adel Elmahdy, Junhyung Ahn, Changho Suh, Soheil Mohajer

ECML-PKDD 2020 Reprogramming GANs via Input Noise Design Kangwook Lee, Changho Suh, Kannan Ramchandran

AAAI 2019 Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh

NeurIPS 2018 Binary Rating Estimation with Graph Side Information Kwangjun Ahn, Kangwook Lee, Hyunseung Cha, Changho Suh

ICLR 2018 Simulated+Unsupervised Learning with Adaptive Data Generation and Bidirectional Mappings Kangwook Lee, Hoon Kim, Changho Suh

ICML 2017 Active Learning for Top-$k$ Rank Aggregation from Noisy Comparisons Soheil Mohajer, Changho Suh, Adel Elmahdy

NeurIPS 2017 Optimal Sample Complexity of M-Wise Data for Top-K Ranking Minje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh

ICML 2016 Community Recovery in Graphs with Locality Yuxin Chen, Govinda Kamath, Changho Suh, David Tse

ICML 2015 Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons Yuxin Chen, Changho Suh