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Yunbum Kook
Yunbum Kook
Verified email at gatech.edu - Homepage
Title
Cited by
Cited by
Year
Incremental lossless graph summarization
J Ko, Y Kook, K Shin
International Conference on Knowledge Discovery & Data Mining (KDD'20), 317-327, 2020
452020
Evolution of real-world hypergraphs: Patterns and models without oracles
Y Kook, J Ko, K Shin
International Conference on Data Mining (ICDM'20), 272-281, 2020
282020
Sampling with Riemannian Hamiltonian Monte Carlo in a constrained space
Y Kook, YT Lee, R Shen, S Vempala
Advances in Neural Information Processing Systems (NeurIPS'22) 35, 31684-31696, 2022
272022
Vertex sparsification for edge connectivity
P Chalermsook, S Das, Y Kook, B Laekhanukit, YP Liu, R Peng, M Sellke, ...
Symposium on Discrete Algorithms (SODA'21), 1206-1225, 2021
212021
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators
Y Kook, YT Lee, R Shen, S Vempala
Conference on Learning Theory (COLT'23), 4504-4569, 2023
102023
Growth patterns and models of real-world hypergraphs
J Ko, Y Kook, K Shin
Knowledge and Information Systems (KAIS) 64 (11), 2883-2920, 2022
102022
Sampling from the Mean-Field Stationary Distribution
Y Kook, MS Zhang, S Chewi, MA Erdogdu, MB Li
arXiv preprint arXiv:2402.07355, 2024
32024
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
K Ahn, Z Zhang, Y Kook, Y Dai
arXiv preprint arXiv:2402.01567, 2024
22024
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies
Y Kook, SS Vempala, MS Zhang
arXiv preprint arXiv:2405.01425, 2024
2024
Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling
Y Kook, SS Vempala
arXiv preprint arXiv:2307.12943, 2023
2023
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Articles 1–10