LY Corporation R&D

Our papers have been accepted at The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025) (external link).

• Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization
  Shogo Iwazaki

• Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
  Runze Yan (Emory University), Xun Shen (Tokyo University of Agriculture and Technology), Akifumi Wachi, Sebastien Gros (Norwegian University of Science and Technology), Anni Zhao (Emory University), Xiao Hu (Emory University)

• Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
  Shogo Iwazaki


• A Provable Approach for End-to-End Safe Reinforcement Learning
  Akifumi Wachi, Kohei Miyaguchi, Takumi Tanabe, Rei Sato, Youhei Akimoto (University of Tsukuba, RIKEN AIP)