Jongha Jon Ryu

18 papers A* 6B 1Journal 10
YearRankTypeTitle / Venue / Authors
2025 A* conf
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation.
ICML
Jongha Jon Ryu, Abhin Shah, Gregory W. Wornell
2025 J jnl
Alignment as Distribution Learning: Your Preference Model is Explicitly a Language Model.
CoRR
Jihun Yun, Juno Kim, Jongho Park, Junhyuck Kim, Jongha Jon Ryu, Jaewoong Cho, Kwang-Sung Jun
2025 J jnl
Contrastive Predictive Coding Done Right for Mutual Information Estimation.
CoRR
Jongha Jon Ryu, Pavan Yeddanapudi, Xiangxiang Xu, Gregory W. Wornell
2025 J jnl
Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems.
CoRR
Minchan Jeong, Jongha Jon Ryu, Se-Young Yun, Gregory W. Wornell
2025 A* conf
Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing.
COLT
Jongha Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun
2025 J jnl
Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing.
CoRR
Jongha Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun
2025 A* conf
Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions.
ICML
Tejas Jayashankar, Jongha Jon Ryu, Gregory W. Wornell
2025 J jnl
Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions.
CoRR
Tejas Jayashankar, Jongha Jon Ryu, Gregory W. Wornell
2024 J jnl
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation.
CoRR
Jongha Jon Ryu, Abhin Shah, Gregory W. Wornell
2024 A* conf
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
NeurIPS
Maohao Shen, Jongha Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
2024 A* conf
Gambling-Based Confidence Sequences for Bounded Random Vectors.
ICML
Jongha Jon Ryu, Gregory W. Wornell
2024 J jnl
Gambling-Based Confidence Sequences for Bounded Random Vectors.
CoRR
Jongha Jon Ryu, Gregory W. Wornell
2024 B conf
Group Fairness with Uncertain Sensitive Attributes.
ISIT
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
2024 J jnl
Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions.
CoRR
Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
2024 A* conf
Operator SVD with Neural Networks via Nested Low-Rank Approximation.
ICML
Jongha Jon Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell
2024 J jnl
Operator SVD with Neural Networks via Nested Low-Rank Approximation.
CoRR
Jongha Jon Ryu, Xiangxiang Xu, H. S. Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell
2023 J jnl
Group Fairness with Uncertainty in Sensitive Attributes.
CoRR
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
2022 — —
From Information Theory to Machine Learning Algorithms: A Few Vignettes
Jongha Jon Ryu