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Augmenting Proximity Graphs for Single-Source Navigability in ANN Search

MS thesis, NYU Tandon School of Engineering, 2026. Advised by Prof. Torsten Suel.

Thesis PDF · Defense slides · C++ implementation · Interactive demo

Graph-based ANN indexes (Vamana, HNSW, NSG) answer queries by greedy traversal: start at an entry point, move to whichever neighbor is closest to the query, stop at a local minimum. Navigability asks whether that traversal can actually reach a given target. The monotone RNG guarantees this from every node, but is far too expensive to build on real datasets — and the guarantee is stronger than necessary, since practical indexes always search from one fixed entry point.

So the thesis asks: what do you gain by guaranteeing navigability only from the designated entry point?

  • a formalization of single-source navigability for directed proximity graphs
  • construction algorithms that enforce it by augmenting a baseline graph with extra edges
  • analysis of the augmented structure, and optimizations that close the gap between the theoretical construction and practical performance
  • experiments on SIFT-small: the final algorithm beats state-of-the-art Vamana construction on the computation-recall tradeoff in some parameter regimes, for both in-graph and out-of-sample queries

Building

Needs a TeX distribution with pdflatex and bibtex.

make          # thesis -> main.pdf
make slides   # defense slides -> slides.pdf

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MS thesis: Augmenting Proximity Graphs for Single-Source Navigability in ANN Search (NYU, 2026)

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