1,700 research outputs found

    Finding the Median (Obliviously) with Bounded Space

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    We prove that any oblivious algorithm using space SS to find the median of a list of nn integers from {1,...,2n}\{1,...,2n\} requires time Ω(nloglogSn)\Omega(n \log\log_S n). This bound also applies to the problem of determining whether the median is odd or even. It is nearly optimal since Chan, following Munro and Raman, has shown that there is a (randomized) selection algorithm using only ss registers, each of which can store an input value or O(logn)O(\log n)-bit counter, that makes only O(loglogsn)O(\log\log_s n) passes over the input. The bound also implies a size lower bound for read-once branching programs computing the low order bit of the median and implies the analog of PNPcoNPP \ne NP \cap coNP for length o(nloglogn)o(n \log\log n) oblivious branching programs

    Pseudorandomness for Regular Branching Programs via Fourier Analysis

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    We present an explicit pseudorandom generator for oblivious, read-once, permutation branching programs of constant width that can read their input bits in any order. The seed length is O(log2n)O(\log^2 n), where nn is the length of the branching program. The previous best seed length known for this model was n1/2+o(1)n^{1/2+o(1)}, which follows as a special case of a generator due to Impagliazzo, Meka, and Zuckerman (FOCS 2012) (which gives a seed length of s1/2+o(1)s^{1/2+o(1)} for arbitrary branching programs of size ss). Our techniques also give seed length n1/2+o(1)n^{1/2+o(1)} for general oblivious, read-once branching programs of width 2no(1)2^{n^{o(1)}}, which is incomparable to the results of Impagliazzo et al.Our pseudorandom generator is similar to the one used by Gopalan et al. (FOCS 2012) for read-once CNFs, but the analysis is quite different; ours is based on Fourier analysis of branching programs. In particular, we show that an oblivious, read-once, regular branching program of width ww has Fourier mass at most (2w2)k(2w^2)^k at level kk, independent of the length of the program.Comment: RANDOM 201

    The Random-Query Model and the Memory-Bounded Coupon Collector

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    Deterministic Black-Box Identity Testing π\pi-Ordered Algebraic Branching Programs

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    In this paper we study algebraic branching programs (ABPs) with restrictions on the order and the number of reads of variables in the program. Given a permutation π\pi of nn variables, for a π\pi-ordered ABP (π\pi-OABP), for any directed path pp from source to sink, a variable can appear at most once on pp, and the order in which variables appear on pp must respect π\pi. An ABP AA is said to be of read rr, if any variable appears at most rr times in AA. Our main result pertains to the identity testing problem. Over any field FF and in the black-box model, i.e. given only query access to the polynomial, we have the following result: read rr π\pi-OABP computable polynomials can be tested in \DTIME[2^{O(r\log r \cdot \log^2 n \log\log n)}]. Our next set of results investigates the computational limitations of OABPs. It is shown that any OABP computing the determinant or permanent requires size Ω(2n/n)\Omega(2^n/n) and read Ω(2n/n2)\Omega(2^n/n^2). We give a multilinear polynomial pp in 2n+12n+1 variables over some specifically selected field GG, such that any OABP computing pp must read some variable at least 2n2^n times. We show that the elementary symmetric polynomial of degree rr in nn variables can be computed by a size O(rn)O(rn) read rr OABP, but not by a read (r1)(r-1) OABP, for any 0<2r1n0 < 2r-1 \leq n. Finally, we give an example of a polynomial pp and two variables orders ππ\pi \neq \pi', such that pp can be computed by a read-once π\pi-OABP, but where any π\pi'-OABP computing pp must read some variable at least $2^n

    Communication Complexity and Secure Function Evaluation

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    We suggest two new methodologies for the design of efficient secure protocols, that differ with respect to their underlying computational models. In one methodology we utilize the communication complexity tree (or branching for f and transform it into a secure protocol. In other words, "any function f that can be computed using communication complexity c can be can be computed securely using communication complexity that is polynomial in c and a security parameter". The second methodology uses the circuit computing f, enhanced with look-up tables as its underlying computational model. It is possible to simulate any RAM machine in this model with polylogarithmic blowup. Hence it is possible to start with a computation of f on a RAM machine and transform it into a secure protocol. We show many applications of these new methodologies resulting in protocols efficient either in communication or in computation. In particular, we exemplify a protocol for the "millionaires problem", where two participants want to compare their values but reveal no other information. Our protocol is more efficient than previously known ones in either communication or computation

    Deterministic Identity Testing for Sum of Read-Once Oblivious Arithmetic Branching Programs

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    A read-once oblivious arithmetic branching program (ROABP) is an arithmetic branching program (ABP) where each variable occurs in at most one layer. We give the first polynomial time whitebox identity test for a polynomial computed by a sum of constantly many ROABPs. We also give a corresponding blackbox algorithm with quasi-polynomial time complexity nO(logn)n^{O(\log n)}. In both the cases, our time complexity is double exponential in the number of ROABPs. ROABPs are a generalization of set-multilinear depth-33 circuits. The prior results for the sum of constantly many set-multilinear depth-33 circuits were only slightly better than brute-force, i.e. exponential-time. Our techniques are a new interplay of three concepts for ROABP: low evaluation dimension, basis isolating weight assignment and low-support rank concentration. We relate basis isolation to rank concentration and extend it to a sum of two ROABPs using evaluation dimension (or partial derivatives).Comment: 22 pages, Computational Complexity Conference, 201
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