2 citations · 5 across the 9 of their papers we have counts for
5 papers · 1 filter
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.…
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
Hao Qin, Kwang-Sung Jun, Chicheng Zhang
We study -armed bandit problems where the reward distributions of the arms are all supported on the interval. It has been a challenge to design regret-efficient randomiz…
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 where is a fixed scalar function, ar…
Revisiting Simple Regret: Fast Rates for Returning a Good Arm
Yao Zhao, Connor James Stephens, Csaba Szepesvári +1
Simple regret is a natural and parameter-free performance criterion for pure exploration in multi-armed bandits yet is less popular than the probability of missing the best arm or…
Jointly Efficient and Optimal Algorithms for Logistic Bandits
Louis Faury, Marc Abeille, Kwang-Sung Jun +1
Logistic Bandits have recently undergone careful scrutiny by virtue of their combined theoretical and practical relevance. This research effort delivered statistically efficient al…