1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits
Yu Xia, Fang Kong, Tong Yu +4
Web-based applications such as chatbots, search engines and news recommendations continue to grow in scale and complexity with the recent surge in the adoption of LLMs. Online mode…
cs.LG2023
Player-optimal Stable Regret for Bandit Learning in Matching Markets
Fang Kong, Shuai Li
The problem of matching markets has been studied for a long time in the literature due to its wide range of applications. Finding a stable matching is a common equilibrium objectiv…
cs.SI2023★ 1 cited
Online Influence Maximization under Decreasing Cascade Model
Fang Kong, Jize Xie, Baoxiang Wang +2
We study online influence maximization (OIM) under a new model of decreasing cascade (DC). This model is a generalization of the independent cascade (IC) model by considering the c…