3 accepted papers
We study multi-objective optimization over probability distributions in Wasserstein space. Recently, \citet{nguyen2025multiple} introduced Multiple Wasserstein Gradient Descent (MWGraD) algorithm, which exploits the geometric structure of Wasserstein space to jointly optimize multiple objectives. Bu…
We address the optimization problem of simultaneously minimizing multiple objective functionals over a family of probability distributions. This type of Multi-Objective Distributional Optimization commonly arises in machine learning and statistics, with applications in areas such as multiple target
The classification bandit problem aims to determine whether a set of given $K$ arms contains at least $L$ good arms or not. Here, an arm is said to be good if its expected reward is no less than a specified threshold. To solve this problem, we introduce an asymptotically optimal algorithm, named P-t…