11 papers
Learning Partition Trees for Nearest Neighbor Search
Sanjeev Khanna, Ashwin Padaki, Erik Waingarten
We study nearest neighbor search from the perspective of data-driven algorithm design: given a dataset of size and sample access to a query distributio…
Locally Approximating the Top Eigenvector of Bounded Entry Matrices
Nicolas Menand, Erik Waingarten
We provide a local computation algorithm to approximate the top eigenvector of a symmetric matrix with entries between and…
Prune, Don't Rebuild: Efficiently Tuning -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…
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…
Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair
Lorenzo Beretta, Vincent Cohen-Addad, Rajesh Jayaram +1
We give a reduction from -approximate Earth Mover's Distance (EMD) to -approximate Closest Pair (CP). As a consequence, we improve the fastest kno…
Instance-Optimal Uniformity Testing and Tracking
Guy Blanc, Clément L. Canonne, Erik Waingarten
In the uniformity testing task, an algorithm is provided with samples from an unknown probability distribution over a (known) finite domain, and must decide whether it is the unifo…