4 papers
Channel-Aware Selection of Folded Bloom Filters for Distributed Systems
John Cartmell, Mihaela Cardei, Ionut Cardei
Periodic Bloom-filter transmission can impose substantial overhead in communication-constrained distributed systems. Lossless compression preserves membership behavior but provides…
Entropy-Punctured Bloom Filters for Memory-Efficient Machine Learning
John Cartmell, Mihaela Cardei, Ionut Cardei
Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or privacy constraints limit access to…
Privacy-Preserving Distributed Learning in IoT Systems: A Unified Threat Model and Evaluation Framework
John Cartmell, Alexander Williams
The increasing deployment of Internet-of-Things (IoT) devices has accelerated the use of distributed learning frameworks, where data remains local while model updates are shared ac…
Bloom Filter Encoding for Machine Learning
John Cartmell, Mihaela Cardei, Ionut Cardei
We present a method that uses a Bloom filter transform to preprocess data for machine learning. Each sample is encoded into a compact bit-array representation using hash-based enco…