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Jongha Jon Ryu
Jongha Jon Ryu
Postdoctoral Associate at MIT
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Feedback recurrent autoencoder
Y Yang, G Sautière, JJ Ryu, TS Cohen
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
242020
Energy-based sequence gans for recommendation and their connection to imitation learning
J Yoo, H Ha, J Yi, J Ryu, C Kim, JW Ha, YH Kim, S Yoon
arXiv preprint arXiv:1706.09200, 2017
122017
Variations on a Theme by Liu, Cuff, and Verdu: The Power of Posterior Sampling
A Bhatt, JT Huang, YH Kim, JJ Ryu, P Sen
The IEEE Information Theory Workshop, pp. 290–294, 2018
102018
Nearest neighbor density functional estimation from inverse Laplace transform
JJ Ryu, S Ganguly, YH Kim, YK Noh, DD Lee
IEEE Transactions on Information Theory 68 (6), 3511-3551, 2022
92022
Monte Carlo methods for randomized likelihood decoding
A Bhatt, JT Huang, YH Kim, JJ Ryu, P Sen
The 56th Annual Allerton Conference on Communication, Control, and Computing, 2018
92018
On universal portfolios with continuous side information
A Bhatt, JJ Ryu, YH Kim
International Conference on Artificial Intelligence and Statistics, 4147-4163, 2023
52023
On confidence sequences for bounded random processes via universal gambling strategies
JJ Ryu, A Bhatt
arXiv preprint arXiv:2207.12382, 2022
52022
Conditional distribution learning with neural networks and its application to universal image denoising
J Ryu, YH Kim
2018 25th IEEE International Conference on Image Processing (ICIP), 3214-3218, 2018
42018
Group fairness with uncertainty in sensitive attributes
A Shah, M Shen, JJ Ryu, S Das, P Sattigeri, Y Bu, GW Wornell
ISIT 2024, 2024
22024
Parameter-free online linear optimization with side information via universal coin betting
JJ Ryu, A Bhatt, YH Kim
AISTATS 2022 151, 6022-6044, 2022
22022
Wyner VAE: Joint and Conditional Generation with Succinct Common Representation Learning
JJ Ryu, Y Choi, YH Kim, M El-Khamy, J Lee
May 27, 1-24, 2019
2*2019
Learning with Succinct Common Representation Based on Wyner's Common Information
JJ Ryu, Y Choi, YH Kim, M El-Khamy, J Lee
arXiv preprint arXiv:1905.10945, 2019
12019
Variational Inference via a Joint Latent Variable Model with Common Information Extraction
JJ Ryu, YH Kim, Y Choi, M El-Khamy, J Lee
Third Workshop on Bayesian Deep Learning (NeurIPS 2018), Montréal, Canada, 1-8, 2018
12018
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
M Shen, JJ Ryu, S Ghosh, Y Bu, P Sattigeri, S Das, GW Wornell
arXiv e-prints, arXiv: 2402.06160, 2024
2024
Gambling-Based Confidence Sequences for Bounded Random Vectors
JJ Ryu, GW Wornell
ICML 2024, 2024
2024
Operator SVD with Neural Networks via Nested Low-Rank Approximation
JJ Ryu, X Xu, HS Erol, Y Bu, L Zheng, GW Wornell
ICML 2024, 2024
2024
An Information-Theoretic Proof of the Kac--Bernstein Theorem
JJ Ryu, YH Kim
arXiv preprint arXiv:2202.06005, 2022
2022
One-Nearest-Neighbor Search is All You Need for Minimax Optimal Regression and Classification
JJ Ryu, YH Kim
arXiv preprint arXiv:2202.02464, 2022
2022
From Information Theory to Machine Learning Algorithms: A Few Vignettes
JJ Ryu
University of California, San Diego, 2022
2022
On the Role of Eigendecomposition in Kernel Embedding
JJ Ryu, JT Huang, YH Kim
2021 IEEE International Symposium on Information Theory (ISIT), 2030-2035, 2021
2021
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