4 papers
Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization
Yuqi Huang, Vincent Y. F. Tan, Sharu Theresa Jose
We investigate Gaussian process (GP) bandit optimization with quantum kernels, assuming the mean reward function lies in the reproducing kernel Hilbert space (RKHS) induced by the…
Almost Asymptotically Optimal Active Clustering Through Pairwise Observations
Rachel S. Y. Teo, P. N. Karthik, Ramya Korlakai Vinayak +1
We propose a new analysis framework for clustering items into an unknown number of distinct groups using noisy and actively collected responses. At each time step, an agent…
Quantum-Enhanced Neural Contextual Bandit Algorithms
Yuqi Huang, Vincent Y. F Tan, Sharu Theresa Jose
Stochastic contextual bandits are fundamental for sequential decision-making but pose significant challenges for existing neural network-based algorithms, particularly when scaling…
Stochastic Bandits for Egalitarian Assignment
Eugene Lim, Vincent Y. F. Tan, Harold Soh
We study EgalMAB, an egalitarian assignment problem in the context of stochastic multi-armed bandits. In EgalMAB, an agent is tasked with assigning a set of users to arms. At each…