עופר נימן

אקדמי בכיר

Near linear lower bound for dimension reduction in ℓ1

Alexandr Andoni, Moses S. Charikar, Ofer Neiman, Huy L. Nguyen

Given a set of n points in ℓ1, how many dimensions are needed to represent all pair wise distances within a specific distortion? This dimension-distortion tradeoff question is well understood for the ℓ1 norm, where O((log n)/ε2) dimensions suffice to achieve 1+ε distortion. In sharp contrast, there is a significant gap between upper and lower bounds for dimension reduction in ℓ1. A recent result shows that distortion 1+ε can be achieved with n/ε2 dimensions. On the other hand, the only lower bounds known are that distortion δ requires nΩ(1/δ2) dimensions and that distortion 1+ε requires n1/2-O(ε log(1/ε)) dimensions. In this work, we show the first near linear lower bounds for dimension reduction in ℓ1. In particular, we show that 1+ε distortion requires at least n1-O(1/log(1/ε)) dimensions. Our proofs are combinatorial, but inspired by linear programming. In fact, our techniques lead to a simple combinatorial argument that is equivalent to the LP based proof of Brinkman-Charikar for lower bounds on dimension reduction in ℓ1.

שפת פרסום אנגלית
דפים 315-323
סטטוס פרסום פורסם - 01.01.2011
מספר מאמר 6108191

Keywords

dimension reduction
metric embedding

ASJC Scopus subject areas

General Computer Science
גישה למסמך
10.1109/FOCS.2011.87
קבצים וקישורים אחרים
Link to publication in Scopus