Kwang-Sung Jun

activity

20202023

most citedImproved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits

2 citations · 5 across the 9 of their papers we have counts for

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Showing 2023Show all

3 papers · 1 filter

cs.LG2023★ 1 cited

Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search

Reyan Ahmed, Mithun Ghosh, Kwang-Sung Jun +1

Graph neural networks are useful for learning problems, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem.…

cs.LG2023

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards

Hao Qin, Kwang-Sung Jun, Chicheng Zhang

We study $K$ -armed bandit problems where the reward distributions of the arms are all supported on the $[0, 1]$ interval. It has been a challenge to design regret-efficient randomiz…

cs.LG2023★ 2 cited

Tighter PAC-Bayes Bounds Through Coin-Betting

Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij +1

We consider the problem of estimating the mean of a sequence of random elements $f (X_{1}, θ)$ $, \dots,$ $f (X_{n}, θ)$ where $f$ is a fixed scalar function, $S = (X_{1}, \dots, X_{n})$ ar…