25 citations · 25 across the 3 of their papers we have counts for
4 papers
JointMatch: A Unified Heterogeneous Graph Neural Solver for Large-Scale Ride-Sharing Matching
Kun Zhao, Xu Chen
Ride-sharing platforms must continuously decide which open requests to bundle into shared trips and which idle vehicles should serve them. The dominant academic approach decomposes…
Multi-Agent Privacy Game in Federated Learning: A Unified Mean-Field View
Kun Zhao, Xu Chen
Federated learning enables collaborative model training across distributed clients without centralising their data, yet privacy remains a persistent concern because the shared mode…
All in One: Generative Modeling as Mean-Field Game Design
Kun Zhao, Xu Chen
Mean-field games (MFGs) offer a unifying lens on continuous-time generative modeling: a cost tuple recovering twelve prominent models---Continuous Normalizing Flows, OT-Flow, Score…
DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset
Weijie Liu, Xiaoxi Zhang, Jingpu Duan +3
Federated Learning (FL) is a distributed learning paradigm that can coordinate heterogeneous edge devices to perform model training without sharing private data. While prior works…