Takemori, Sho

10 publications

ICML 2025 Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms Sho Takemori, Yuhei Umeda, Aditya Gopalan

AAAI 2025 Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization Nobuo Namura, Sho Takemori

AISTATS 2024 Model-Based Best Arm Identification for Decreasing Bandits Sho Takemori, Yuhei Umeda, Aditya Gopalan

UAI 2024 Quantum Kernelized Bandits Yasunari Hikima, Kazunori Murao, Sho Takemori, Yuhei Umeda

ICLR 2024 Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan

ICMLW 2023 SelMix: Selective Mixup Fine Tuning for Optimizing Non-Decomposable Metrics Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan

NeurIPS 2022 Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics Harsh Rangwani, Shrinivas Ramasubramanian, Sho Takemori, Kato Takashi, Yuhei Umeda, Venkatesh Babu R

ICML 2022 Distributionally-Aware Kernelized Bandit Problems for Risk Aversion Sho Takemori

ICML 2021 Approximation Theory Based Methods for RKHS Bandits Sho Takemori, Masahiro Sato

UAI 2020 Submodular Bandit Problem Under Multiple Constraints Sho Takemori, Masahiro Sato, Takashi Sonoda, Janmajay Singh, Tomoko Ohkuma