MaxSketch achieves O~(log n / ε²) memory for (1+ε)-approximate distinct counting in streams with geometric structure via max-linear random projections.
Approximate nearest neighbors: towards removing the curse of dimensionality
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
representative citing papers
OPT-SNG introduces a martingale model for SNG pruning in ANNS, proves O(n^{2/3+ε}) max out-degree and O(log n) expected path length, and gives a closed-form optimal truncation parameter that yields 5.9× average construction speedup.
citing papers explorer
-
MaxSketch: Robust Distinct Counting in Streams via Random Projections
MaxSketch achieves O~(log n / ε²) memory for (1+ε)-approximate distinct counting in streams with geometric structure via max-linear random projections.
-
Sparse Neighborhood Graph-Based Approximate Nearest Neighbor Search Revisited: Theoretical Analysis and Optimization
OPT-SNG introduces a martingale model for SNG pruning in ANNS, proves O(n^{2/3+ε}) max out-degree and O(log n) expected path length, and gives a closed-form optimal truncation parameter that yields 5.9× average construction speedup.