Dasgupta, Sanjoy; Gupta, Anupam An elementary proof of a theorem of Johnson and Lindenstrauss. (English) Zbl 1018.51010 Random Struct. Algorithms 22, No. 1, 60-65 (2003). Summary: A result of W. B. Johnson and J. Lindenstrauss [Contemp. Math. 26, 189-206 (1984; Zbl 0539.46017)] shows that a set of \(n\) points in high dimensional Euclidean space can be mapped into an \(O(\log n/ \varepsilon^2)\)-dimensional Euclidean space such that the distance between any two points changes by only a factor of \((1\pm \varepsilon)\). In this note, we prove this theorem using elementary probabilistic techniques. Cited in 1 ReviewCited in 129 Documents MathOverflow Questions: Johnson-Lindenstrauss Lemma on \(S^{d-1}\) MSC: 51K05 General theory of distance geometry 68W20 Randomized algorithms Keywords:Euclidean space; distance Citations:Zbl 0539.46017 × Cite Format Result Cite Review PDF Full Text: DOI References: [1] Problems and results in extremal combinatorics, Part I, unpublished manuscript. [2] Database friendly random projections, Proc 20th ACM Symp Principles of Database Systems, Santa Barbara, CA, 2001, 274-281. [3] and An algorithmic theory of learning: Robust concepts and random projection, Proc 40th Annu IEEE Symp Foundations of Computer Science, New York, NY, 1999, pp. 616-623. [4] Chernoff, Ann Math Stat 23 pp 493– (1952) [5] Learning mixtures of Gaussians, Proc 40th Annu IEEE Symp Foundations of Computer Science, New York, NY, 1999, pp. 634-644. [6] and Derandomized dimensionality reduction with applications, Proc 13th Annu ACM SIAM Symp Discrete Algorithms, San Francisco, CA, 2002, pp. 705-712. · Zbl 1093.68668 [7] Frankl, J Combin Theory Ser B 44 pp 355– (1988) [8] Frankl, Ann Inst Stat Math 42 pp 463– (1990) [9] Hoeffding, J Am Stat Assoc 58 pp 13– (1963) [10] and Approximate nearest neighbors: Towards removing the curse of dimensionality, Proc 30th Annu ACM Symp Theory of Computing, Dallas, TX, 1998, pp. 604-613. · Zbl 1029.68541 [11] Johnson, Contemp Math 26 pp 189– (1984) [12] Linial, Combinatorica 15 pp 215– (1995) [13] Algorithmic derandomization using complexity theory, Proc 34th Annu ACM Symp Theory of Computing, Montréal, Canada, 2002, pp. 619-626. · Zbl 1192.68303 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.