collaborators

7 papers

cs.DC2026

Fast Multidimensional Approximate Agreement with Optimal Resilience Using Ball Validity

Tijana Milentijević, Stefan Schmid

Multidimensional approximate agreement requires processes with inputs in to output vectors close to each other, despite up to Byzantine faults. Under convex…

cs.DS2026

Privacy Attacks on Stable Marriage

Stephan A. Fahrenkrog-Petersen, Aleksander Figiel, Darya Melnyk +2

The stable marriage problem appears in many privacy-sensitive domains, for example in the National Resident Matching Program in the US. In such applications, preserving the privacy…

cs.DC2026

Resilient Byzantine Agreement with Predictions

Julien Dallot, Darya Melnyk, Tijana Milentijevic +2

This paper studies the Byzantine Agreement problem where the nodes have access to a predictor that flags nodes for suspicion of faulty (Byzantine) behavior. We focus on algorithmic…

cs.LG2026

Practical Validity Conditions for Byzantine-Tolerant Federated Learning

Mélanie Cambus, Darya Melnyk, Tijana Milentijević +1

Robust aggregation is the core operation in Byzantine-tolerant federated learning. To ensure the quality of aggregation independently of data distribution or attacks, validity cond…

cs.NI2026

The Carrier Pigeon Internet Protocol: An Algorithmic (and Lighthearted) Perspective

Matthias Bentert, Shay Kutten, Darya Melnyk +2

The theoretical model behind the pigeon post as a link layer in a communication network was introduced by Shannon (under the guise of studying One-Time Pads for cryptography). That…

cs.LG2025

Centroid Approximation for Byzantine-Tolerant Federated Learning

Mélanie Cambus, Darya Melnyk, Tijana Milentijević +1

Federated learning allows each client to keep its data locally when training machine learning models in a distributed setting. Significant recent research established the requireme…