GenLabel: Mixup Relabeling using Generative Models
J. Sohn, L. Shang, H. Chen, J. Moon, D. Papailiopoulos, and K. Lee
ICML 2022
Permutation-Based SGD: Is Random Optimal?
S. Rajput, K. Lee, and D. Papailiopoulos
ICLR 2022
Sample Selection for Fair and Robust Training
Y. Roh, K. Lee, S. Whang, and C. Suh
NeurIPS 2021
J. Kim, J. Jeon, K. Lee, S. Oh, and J. Ok
Gradient Inversion with Generative Image Prior
NeurIPS 2021
Coded-InvNet for Resilient Prediction Serving Systems
T. Dinh, and K. Lee
ICML 2021 (long oral)
Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
C. Jo, and K. Lee
ICML 2021
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification
S. Agarwal, H. Wang, K. Lee, S. Venkataraman, and D. Papailiopoulos
MLSys 2021
FairBatch: Batch Selection for Model Fairness
Y. Roh, K. Lee, S. Whang, and C. Suh
ICLR 2021
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J. Sohn, K. Lee, and D. Papailiopoulos
NeurIPS 2020
Reprogramming GANs via Input Noise Design
K. Lee, C. Suh, and K. Ramchandran
ECML PKDD 2020
FR-Train: A mutual information-based approach to fair and robust training
Y. Roh, K. Lee, S. Whang, and C. Suh
ICML 2020
Crash to Not Crash: Learn to Identify Dangerous Vehicles using a Simulator
H. Kim*, K. Lee*, G. Hwang, and C. Suh
AAAI 2019 (oral)
Binary Rating Estimation with Graph Side Information
K. Ahn, K. Lee, H. Cha, and C. Suh
NeurIPS 2018
Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings
K. Lee*, H. Kim*, and C. Suh
ICLR 2018