4 papers · 1 filter
Learning with Posterior Sampling for Revenue Management under Time-varying Demand
Kazuma Shimizu, Junya Honda, Shinji Ito +1
This paper discusses the revenue management (RM) problem to maximize revenue by pricing items or services. One challenge in this problem is that the demand distribution is unknown…
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
Shinji Ito, Taira Tsuchiya, Junya Honda
Follow-The-Regularized-Leader (FTRL) is known as an effective and versatile approach in online learning, where appropriate choice of the learning rate is crucial for smaller regret…
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
Jongyeong Lee, Junya Honda, Shinji Ito +1
This paper studies the optimality of the Follow-the-Perturbed-Leader (FTPL) policy in both adversarial and stochastic -armed bandits. Despite the widespread use of the Follow-th…
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
Taira Tsuchiya, Shinji Ito, Junya Honda
Partial monitoring is a generic framework of online decision-making problems with limited feedback. To make decisions from such limited feedback, it is necessary to find an appropr…