Jongha Jon Ryu

According to our database, Jongha Jon Ryu authored at least 14 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Contrastive Predictive Coding Done Right for Mutual Information Estimation.

Jongha Jon Ryu, Pavan Yeddanapudi, Xiangxiang Xu, Gregory W. Wornell

CoRR, October, 2025

Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems.

Minchan Jeong, Jongha Jon Ryu, Se-Young Yun, Gregory W. Wornell

CoRR, July, 2025

Alignment as Distribution Learning: Your Preference Model is Explicitly a Language Model.

Jihun Yun, Juno Kim, Jongho Park, Junhyuck Kim, Jongha Jon Ryu, Jaewoong Cho, Kwang-Sung Jun

CoRR, June, 2025

Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions.

Tejas Jayashankar, Jongha Jon Ryu, Gregory W. Wornell

CoRR, February, 2025

A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation.

Jongha Jon Ryu, Abhin Shah, Gregory W. Wornell

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions.

Tejas Jayashankar, Jongha Jon Ryu, Gregory W. Wornell

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing.

Jongha Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions.

Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell

CoRR, 2024

Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?

Maohao Shen, Jongha Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Group Fairness with Uncertain Sensitive Attributes.

Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell

Proceedings of the IEEE International Symposium on Information Theory, 2024

Gambling-Based Confidence Sequences for Bounded Random Vectors.

Jongha Jon Ryu, Gregory W. Wornell

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Operator SVD with Neural Networks via Nested Low-Rank Approximation.

Jongha Jon Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Group Fairness with Uncertainty in Sensitive Attributes.

Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell

CoRR, 2023

2022

From Information Theory to Machine Learning Algorithms: A Few Vignettes

Jongha Jon Ryu

PhD thesis, 2022