2 citations · 3 across the 6 of their papers we have counts for
6 papers
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…
Your Neighbors Know: Leveraging Local Neighborhoods for Backdoor Detection in Decentralized Learning
Sayan Biswas, Antoine Boutet, Davide Frey +7
Decentralized learning (DL) is an emerging machine learning paradigm where nodes collaboratively train models without a central server. However, the collaborative nature of DL make…
Optimizing Agentic Workflows using Meta-tools
Sami Abuzakuk, Anne-Marie Kermarrec, Rishi Sharma +2
Agentic AI enables LLM to dynamically reason, plan, and interact with tools to solve complex tasks. However, agentic workflows often require many iterative reasoning steps and tool…
Position: Collaborative Agentic AI Needs Interoperability Across Ecosystems
Rishi Sharma, Martijn de Vos, Pradyumna Chari +2
Collaborative agentic AI is projected to transform entire industries by enabling AI-powered agents to autonomously perceive, plan, and act within digital environments. Yet, current…
Fair Decentralized Learning
Sayan Biswas, Anne-Marie Kermarrec, Rishi Sharma +2
Decentralized learning (DL) is an emerging approach that enables nodes to collaboratively train a machine learning model without sharing raw data. In many application domains, such…
PeerSwap: A Peer-Sampler with Randomness Guarantees
Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko +2
The ability of a peer-to-peer (P2P) system to effectively host decentralized applications often relies on the availability of a peer-sampling service, which provides each participa…