17 citations · 39 across the 10 of their papers we have counts for
4 papers · 1 filter
Online Learning with Primary and Secondary Losses
Avrim Blum, Han Shao
We study the problem of online learning with primary and secondary losses. For example, a recruiter making decisions of which job applicants to hire might weigh false positives and…
Stochastic Bandits with Vector Losses: Minimizing -Norm of Relative Losses
Xuedong Shang, Han Shao, Jian Qian
Multi-armed bandits are widely applied in scenarios like recommender systems, for which the goal is to maximize the click rate. However, more factors should be considered, e.g., us…
Structure Adaptive Algorithms for Stochastic Bandits
Rémy Degenne, Han Shao, Wouter M. Koolen
We study reward maximisation in a wide class of structured stochastic multi-armed bandit problems, where the mean rewards of arms satisfy some given structural constraints, e.g. li…
Accurately Solving Physical Systems with Graph Learning
Han Shao, Tassilo Kugelstadt, Torsten Hädrich +4
Iterative solvers are widely used to accurately simulate physical systems. These solvers require initial guesses to generate a sequence of improving approximate solutions. In this…