MCI approximates dense nearest neighbor graphs via maximal clique covers and progressive local densification to support fast arbitrary-filtered approximate nearest neighbor search with reduced space.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
Onyx inverts ANN-ORAM optimization priorities with a compact pruning representation and locality-aware shallow tree to deliver 1.7-9.9x lower cost and 2.3-12.3x lower latency for disk-oblivious ANN search.
An LSH-based system with adaptive bucket probing, progressive sampling, and product quantization estimates cardinality for high-dimensional similarity queries efficiently.
citing papers explorer
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MCI: A Maximal Clique Index for Efficient Arbitrary-Filtered Approximate Nearest Neighbor Search
MCI approximates dense nearest neighbor graphs via maximal clique covers and progressive local densification to support fast arbitrary-filtered approximate nearest neighbor search with reduced space.
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Onyx: Cost-Efficient Disk-Oblivious ANN Search
Onyx inverts ANN-ORAM optimization priorities with a compact pruning representation and locality-aware shallow tree to deliver 1.7-9.9x lower cost and 2.3-12.3x lower latency for disk-oblivious ANN search.
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Cardinality Estimation for High Dimensional Similarity Queries with Adaptive Bucket Probing
An LSH-based system with adaptive bucket probing, progressive sampling, and product quantization estimates cardinality for high-dimensional similarity queries efficiently.