779 research outputs found
Communication Efficient Checking of Big Data Operations
We propose fast probabilistic algorithms with low (i.e., sublinear in the
input size) communication volume to check the correctness of operations in Big
Data processing frameworks and distributed databases. Our checkers cover many
of the commonly used operations, including sum, average, median, and minimum
aggregation, as well as sorting, union, merge, and zip. An experimental
evaluation of our implementation in Thrill (Bingmann et al., 2016) confirms the
low overhead and high failure detection rate predicted by theoretical analysis
A note on Probably Certifiably Correct algorithms
Many optimization problems of interest are known to be intractable, and while
there are often heuristics that are known to work on typical instances, it is
usually not easy to determine a posteriori whether the optimal solution was
found. In this short note, we discuss algorithms that not only solve the
problem on typical instances, but also provide a posteriori certificates of
optimality, probably certifiably correct (PCC) algorithms. As an illustrative
example, we present a fast PCC algorithm for minimum bisection under the
stochastic block model and briefly discuss other examples
On Algebraic Decoding of -ary Reed-Muller and Product-Reed-Solomon Codes
We consider a list decoding algorithm recently proposed by Pellikaan-Wu
\cite{PW2005} for -ary Reed-Muller codes of
length when . A simple and easily accessible
correctness proof is given which shows that this algorithm achieves a relative
error-correction radius of . This is
an improvement over the proof using one-point Algebraic-Geometric codes given
in \cite{PW2005}. The described algorithm can be adapted to decode
Product-Reed-Solomon codes.
We then propose a new low complexity recursive algebraic decoding algorithm
for Reed-Muller and Product-Reed-Solomon codes. Our algorithm achieves a
relative error correction radius of . This technique is then proved to outperform the Pellikaan-Wu
method in both complexity and error correction radius over a wide range of code
rates.Comment: 5 pages, 5 figures, to be presented at 2007 IEEE International
Symposium on Information Theory, Nice, France (ISIT 2007
Secret Sharing Based on a Hard-on-Average Problem
The main goal of this work is to propose the design of secret sharing schemes
based on hard-on-average problems. It includes the description of a new
multiparty protocol whose main application is key management in networks. Its
unconditionally perfect security relies on a discrete mathematics problem
classiffied as DistNP-Complete under the average-case analysis, the so-called
Distributional Matrix Representability Problem. Thanks to the use of the search
version of the mentioned decision problem, the security of the proposed scheme
is guaranteed. Although several secret sharing schemes connected with
combinatorial structures may be found in the bibliography, the main
contribution of this work is the proposal of a new secret sharing scheme based
on a hard-on-average problem, which allows to enlarge the set of tools for
designing more secure cryptographic applications
A Simple Algorithm for Hamiltonicity
We develop a new algebraic technique that solves the following problem: Given
a black box that contains an arithmetic circuit over a field of
characteristic of degree~. Decide whether , expressed as an
equivalent multivariate polynomial, contains a multilinear monomial of degree
.
This problem was solved by Williams \cite{W} and Bj\"orklund et. al.
\cite{BHKK} for a white box (the circuit is given as an input) that contains
arithmetic circuit. We show a simple black box algorithm that solves the
problem with the same time complexity.
This gives a simple randomized algorithm for the simple -path problem for
directed graphs of the same time complexity\footnote{ is
} as in \cite{W} and with reusing the same
ideas from \cite{BHKK} with the above gives another algorithm (probably not
simpler) for undirected graphs of the same time complexity as in
\cite{B10,BHKK}
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