3 papers
cs.DC2026
Efficient and Robust Online Learning to Rank in Decentralized Systems
Marcel Gregoriadis, Martijn de Vos, Sayan Biswas +2
In Online Learning to Rank (OLTR), ranking models are trained directly from live user interactions, but existing systems rely on a trusted central server to collect and process the…
cs.DC2025
SwarmSearch: Decentralized Search Engine with Self-Funding Economy
Marcel Gregoriadis, Rowdy Chotkan, Petru Neague +1
Centralized search engines control what we see, read, believe, and vote. Consequently, they raise concerns over information control, censorship, and bias. Decentralized search engi…
cs.IR2025
A Large-Scale Web Search Dataset for Federated Online Learning to Rank
Marcel Gregoriadis, Jingwei Kang, Johan Pouwelse
The centralized collection of search interaction logs for training ranking models raises significant privacy concerns. Federated Online Learning to Rank (FOLTR) offers a privacy-pr…