Следене
Jongha Jon Ryu
Jongha Jon Ryu
Postdoctoral Associate at MIT
Потвърден имейл адрес: mit.edu - Начална страница
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Позовавания
Позовавания
Година
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 confidence sequences for bounded random processes via universal gambling strategies
JJ Ryu, A Bhatt
IEEE Transactions on Information Theory, 2024
52024
On universal portfolios with continuous side information
A Bhatt, JJ Ryu, YH Kim
International Conference on Artificial Intelligence and Statistics, 4147-4163, 2023
52023
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
32024
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
Gambling-Based Confidence Sequences for Bounded Random Vectors
JJ Ryu, GW Wornell
ICML 2024, 2024
12024
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
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
JJ Ryu, A Shah, GW Wornell
arXiv preprint arXiv:2409.18209, 2024
2024
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
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
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Статии 1–20