Invited talks (2023) The Coordinated Science Laboratory Student Conference, Information Theory and Applications Workshop, Information Theory and Data Science Workshop, UW Madison SILO, Midwest Regional Conferenc, (2022) Samsung Advanced Institute of Technology, EIRIC Korea
Invited talks (2023) US-Mexico Workshop on Optimization and its Applications, (2022) KAIST AI International Symposium, IOS’22, UCSB CCDC, USC EE, (2021) UC Berkeley BLISS
Coded computation
Coded-InvNet (coded computation for deep invertible neural networks): ICML’21
Speeding Up Distributed Machine Learning Using Codes: T-IT’18
The Joint Communications Society/Information Theory Society Paper Award, 2020
Invited talks (2021) Seoul National University, POSTECH AI
New preprints
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization Joseph Shenouda, Rahul Parhi, Kangwook Lee, and Robert D. Nowak Arxiv, 2023
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee Arxiv, 2023
A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets Liu Yang, Jifan Zhang, Joseph Shenouda, Dimitris Papailiopoulos, Kangwook Lee, and Robert D. Nowak Arxiv, NeurIPS’22 OPT Workshop, 2022
Outlier-Robust Group Inference via Gradient Space Clustering Yuchen Zeng, Kristjan Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin Arxiv, 2022