3 citations · 4 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
BSB: Towards Demand-Aware Peer Selection With XOR-based Routing
Qingyun Ji, Darya Melnyk, Arash Pourdamghani +1
Peer-to-peer networks, as a key enabler of modern networked and distributed systems, rely on peer-selection algorithms to optimize their scalability and performance. Peer-selection…
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…
Approximate Agreement Algorithms for Byzantine Collaborative Learning
Mélanie Cambus, Darya Melnyk, Tijana Milentijević +1
In Byzantine collaborative learning, clients in a peer-to-peer network collectively learn a model without sharing their data by exchanging and aggregating stochastic gradient e…
Hash & Adjust: Competitive Demand-Aware Consistent Hashing
Arash Pourdamghani, Chen Avin, Robert Sama +2
Distributed systems often serve dynamic workloads and resource demands evolve over time. Such a temporal behavior stands in contrast to the static and demand-oblivious nature of mo…
SpiderDAN: Matching Augmentation in Demand-Aware Networks
Aleksander Figiel, Darya Melnyk, André Nichterlein +2
Graph augmentation is a fundamental and well-studied problem that arises in network optimization. We consider a new variant of this model motivated by reconfigurable communication…
DecentPeeR: A Self-Incentivised & Inclusive Decentralized Peer Review System
Johannes Gruendler, Darya Melnyk, Arash Pourdamghani +1
Peer review, as a widely used practice to ensure the quality and integrity of publications, lacks a well-defined and common mechanism to self-incentivize virtuous behavior across a…