The Johnson-Lindenstrauss lemma is a fundamental result in probability with several applications in the design and analysis of algorithms in high dimensional geometry. Most known constructions of linear embeddings that satisfy the Johnson-Lindenstrauss property involve randomness. We address the question of explicitly constructing such embedding families and provide a construction with an almost optimal use of randomness: we use O(log(n delta)log(log(n delta) epsilon)) random bits for embedding n dimensions to O(log(1 delta) epsilon^2) dimensions with error probability at most delta, and distortion at most epsilon. In particular, for delta = 1 poly(n) and fixed epsilon, we use O(log n loglog n) random bits. Previous constructions required at least O(log^2 n) random bits to get polynomially small error.
Independently, Kane and Nelson @cite_12 obtained a construction that is similar in spirit to ours and achieves a slightly better seed-length of @math . Note that for the important case of @math polynomially small, our seed-length is the same as theirs.
@cite_12
2099601775 2950183285 2106532429 1967969290
We prove the existence of a polynomial time computable pseudorandom generator that @math -fools constant width regular read-once branching programs of length @math using a seed of length @math . The previous best pseudorandom generator for regular branching programs used a seed of length @math , and was due to Braverman et. al. and Brody and Verbin (FOCS 2010). Our pseudorandom generator is the INW generator due to Impagliazzo et. al. (STOC 1994). Our work shares some similarity with the recent work of Kouck ' y et. al. (STOC 2011)who get similar seed length for permutation branching programs. However, our work proceeds by analyzing the eigenvalues of the stochastic matrices that arise in the transitions of the branching program which arguably makes the technique more robust. As a corollary of our techniques, we present new results on the small biased spaces for group products'' problem by Meka and Zuckerman (RANDOM 2009). We get a pseudorandom generator with seed length @math . Previously, using the result of Kouck ' y et. al., it was possible to get a seed length of @math for this problem. We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for combinatorial rectangles and read-once CNFs and a hitting set generator for width-3 branching programs, all of which achieve near-optimal seed-length even in the low-error regime: We get seed-length O(log (n epsilon)) for error epsilon. Previously, only constructions with seed-length O( ^ 3 2 n) or O( ^2 n) were known for these classes with polynomially small error. The (pseudo)random restrictions we use are milder than those typically used for proving circuit lower bounds in that we only set a constant fraction of the bits at a time. While such restrictions do not simplify the functions drastically, we show that they can be derandomized using small-bias spaces. Motivation: Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. The introduction of optimal spaced seeds in PatternHunter has increased both the sensitivity and the speed of homology search, and it has been adopted by many alignment programs such as BLAST. With the further improvement provided by multiple spaced seeds in PatternHunterII, Smith–Waterman sensitivity is approached at BLASTn speed. However, computing optimal multiple spaced seeds was proved to be NP-hard and current heuristic algorithms are all very slow (exponential). Results: We give a simple algorithm which computes good multiple seeds in polynomial time. Due to a completely different approach, the difference with respect to the previous methods is dramatic. The multiple spaced seed of PatternHunterII, with 16 weight 11 seeds, was computed in 12 days. It takes us 17 s to find a better one. Our approach changes the way of looking at multiple spaced seeds. Contact: [email protected] We prove that the pseudorandom generator introduced by (1994) with proper choice of parameters fools group products of a given finite group G. The seed length is O((|G|O(1) + log 1 δ)log n), where n is the length of the word and δ is the allowed error. The result implies that the pseudorandom generator with seed length O((2O(w log w) + log 1 δ)log n) fools read-once permutation branching programs of width w. As an application of the pseudorandom generator one obtains small-bias spaces for products over all finite groups Meka and Zuckerman (2009).