Hopper: Bounded-Memory Collaborative Debiasing for Byzantine-Tolerant Peer Sampling

arXiv:2609.19893 · cs.CR, cs.DC · Submitted 2026-09-17 · Read on arXiv

cs.CR, cs.DC

Submitted: 2026-09-17

Updated: 2026-09-18

Journal ref: IEEE International Symposium on Network Computing and Applications, Nov 2026, Syracuse, Italy

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

F1 Score — 5× in this paper · explained in 3 episodes
Cold Filter — 4× in this paper
Fidelity — 4× in this paper · explained in 2 episodes
Adaptation — 3× in this paper · explained in 1 episode
Decentralized Learning — 3× in this paper · explained in 2 episodes
Lossy Conservative Update — 3× in this paper
Active Inference — 1× in this paper · explained in 1 episode
Adaptive Sampling — 1× in this paper · explained in 1 episode
Adversarial Model — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Clustering — 1× in this paper · explained in 2 episodes
Consistency — 1× in this paper · explained in 3 episodes
Count-Mean-Min with Conservative Updates — 1× in this paper
Distribution Shift — 1× in this paper · explained in 5 episodes
Online Adaptation — 1× in this paper · explained in 3 episodes
Robustness — 1× in this paper · explained in 5 episodes

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