Yunbum Kook

30 papers A* 13Journal 17
YearRankTypeTitle / Venue / Authors
2025 A* conf
Fast Tensor Completion via Approximate Richardson Iteration.
ICML
Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook, Ali Jadbabaie
2025 J jnl
Fast Tensor Completion via Approximate Richardson Iteration.
CoRR
Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook, Ali Jadbabaie
2025 A* conf
Faster Logconcave Sampling from a Cold Start in High Dimension.
FOCS
Yunbum Kook, Santosh S. Vempala
2025 J jnl
Faster logconcave sampling from a cold start in high dimension.
CoRR
Yunbum Kook, Santosh S. Vempala
2025 A* conf
Rényi-infinity constrained sampling with
SODA
Yunbum Kook, Matthew S. Zhang
2025 A* conf
Sampling and Integration of Logconcave Functions by Algorithmic Diffusion.
STOC
Yunbum Kook, Santosh S. Vempala
2025 J jnl
The Localization Method for High-Dimensional Inequalities.
CoRR
Yunbum Kook, Santosh S. Vempala
2025 J jnl
Zeroth-order log-concave sampling.
CoRR
Yunbum Kook
2024 J jnl
Covariance estimation using Markov chain Monte Carlo.
CoRR
Yunbum Kook, Matthew S. Zhang
2024 A* conf
Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling.
COLT
Yunbum Kook, Santosh S. Vempala
2024 A* conf
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies.
NeurIPS
Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang
2024 J jnl
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies.
CoRR
Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang
2024 J jnl
Rényi-infinity constrained sampling with d
CoRR
Yunbum Kook, Matthew S. Zhang
2024 J jnl
Sampling and Integration of Logconcave Functions by Algorithmic Diffusion.
CoRR
Yunbum Kook, Santosh S. Vempala
2024 A* conf
Sampling from the Mean-Field Stationary Distribution.
COLT
Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li
2024 J jnl
Sampling from the Mean-Field Stationary Distribution.
CoRR
Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan Bill Li
2024 A* conf
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise.
ICML
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook, Yan Dai
2024 J jnl
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise.
CoRR
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook, Yan Dai
2023 A* conf
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators.
COLT
Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2023 J jnl
Efficiently Sampling the PSD Cone with the Metric Dikin Walk.
CoRR
Yunbum Kook, Santosh S. Vempala
2022 J jnl
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators.
CoRR
Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2022 J jnl
Growth patterns and models of real-world hypergraphs.
Knowl. Inf. Syst.
Jihoon Ko, Yunbum Kook, Kijung Shin
2022 A* conf
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space.
NeurIPS
Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2022 J jnl
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space.
CoRR
Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2021 A* conf
Vertex Sparsification for Edge Connectivity.
SODA
Parinya Chalermsook, Syamantak Das, Yunbum Kook, Bundit Laekhanukit, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz
2020 A* conf
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles.
ICDM
Yunbum Kook, Jihoon Ko, Kijung Shin
2020 J jnl
Evolution of Real-world Hypergraphs: Patterns and Models without Oracles.
CoRR
Yunbum Kook, Jihoon Ko, Kijung Shin
2020 A* conf
Incremental Lossless Graph Summarization.
KDD
Jihoon Ko, Yunbum Kook, Kijung Shin
2020 J jnl
Incremental Lossless Graph Summarization.
CoRR
Jihoon Ko, Yunbum Kook, Kijung Shin
2020 J jnl
Vertex Sparsification for Edge Connectivity.
CoRR
Parinya Chalermsook, Syamantak Das, Bundit Laekhanukit, Yunbum Kook, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz