#bloom-filters News & Analysis

2 articles tagged with #bloom-filters. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 235/10

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Learning Filters with Certainty

Researchers propose enhancing Counting Bloom Filters (CBFs) by leveraging certainty signals from hash collision information to improve machine learning model accuracy. This work demonstrates how traditional data structure design can be refined to provide probabilistic confidence metrics, enabling hybrid ML-filter architectures to make more informed decisions in applications like caching and anomaly detection.

AINeutralarXiv – CS AI · May 286/10

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GONDOR to the Rescue: Satisficing Planning with Low Memory

Researchers introduce GONDOR, a memory-efficient extension of Greedy Best-First Search that enables planning algorithms to operate under strict memory constraints by compressing search trees while retaining sparse anchor states. The algorithm reconstructs paths through re-searching between these states, with experiments showing consistent improvements in coverage on low-memory devices compared to standard approaches.