Ashwin Padaki

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cs.DS2026

Prune, Don't Rebuild: Efficiently Tuning $α$ -Reachable Graphs for Nearest Neighbor Search

Tian Zhang, Ashwin Padaki, Jiaming Liang +2

Vector similarity search is an essential primitive in modern AI and ML applications. Most vector databases adopt graph-based approximate nearest neighbor (ANN) search algorithms, s…

cs.DS2025

A Polynomial Space Lower Bound for Diameter Estimation in Dynamic Streams

Sanjeev Khanna, Ashwin Padaki, Krish Singal +1

We study the space complexity of estimating the diameter of a subset of points in an arbitrary metric space in the dynamic (turnstile) streaming model. The input is given as a stre…

cs.DS2025

Sparse Navigable Graphs for Nearest Neighbor Search: Algorithms and Hardness

Sanjeev Khanna, Ashwin Padaki, Erik Waingarten

We initiate the study of approximation algorithms and computational barriers for constructing sparse $α$ -navigable graphs [IX23, DGM+24], a core primitive underlying recent advance…

Prune, Don't Rebuild: Efficiently Tuning α-Reachable Graphs for Nearest Neighbor Search

A Polynomial Space Lower Bound for Diameter Estimation in Dynamic Streams

Sparse Navigable Graphs for Nearest Neighbor Search: Algorithms and Hardness

Prune, Don't Rebuild: Efficiently Tuning $α$ -Reachable Graphs for Nearest Neighbor Search