4 papers
Local Epochs as Optimal Stopping: Theory and Evidence in Federated Learning
Ke Xiao, Qiyuan Wang, Christos Anagnostopoulos
How long should each client train before communicating? Federated learning usually answers with a fixed, hand-tuned number of local epochs, yet an extra epoch helps only while the…
SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning
Ke Xiao, Qiyuan Wang, Christos Anagnostopoulos
Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under uncertainty. Fixed probe budgets…
An End-to-End Approach for Fixing Concurrency Bugs via SHB-Based Context Extractor
Zhuang Li, Qiuping Yi, Keyang Xiao +2
With the rise of multi-core processors and distributed systems, concurrent programming has become essential yet challenging, primarily due to the non-deterministic nature of thread…
Operational Runtime Behavior Mining for Open-Source Supply Chain Security
Zhuoran Tan, Ke Xiao, Jeremy Singer +1
Open-source software (OSS) is a critical component of modern software systems, yet supply chain security remains challenging in practice due to unavailable or obfuscated source cod…