Results 1  10
of
530,140
STOCHASTIC COALESCENCE IN LOGARITHMIC TIME
"... Abstract. The following distributed coalescence protocol was introduced by Dahlia Malkhi in 2006 motivated by applications in social networking. Initially there are n agents wishing to coalesce into one cluster via a decentralized stochastic process, where each round is as follows: Every cluster fli ..."
Abstract
 Add to MetaCart
. Empirical results by Fernandess and Malkhi suggested the protocol concludes in O(log n) rounds with high probability, whereas numerical estimates by Oded Schramm, based on an ingenious analytic approximation, suggested that the coalescence time should be superlogarithmic. Our contribution is a rigorous
kinetics with logarithmic time update
, 2014
"... In this paper I outline a fast method called KFOLD for implementing the Gillepie algorithm to stochastically sample the folding kinetics of an RNA molecule at single basepair resolution. In the same fashion as the KINFOLD algorithm, which also uses the Gillespie algorithm to predict folding kineti ..."
Abstract
 Add to MetaCart
/deletion reactions and their corresponding rates do not change between each step in the algorithm. This allows KFOLD to achieve a substantial speedup in the time required to compute a prediction of the folding pathway and, for a fixed number of basepair moves, performs logarithmically with sequence size
Maintaining partial sums in logarithmic time
"... We present a data structure that allows to maintain in logarithmic time all partial sums of elements of a linear array during incremental changes of elementâ€™s values. Key words: Partial sums; Data structures; Algorithms 1 ..."
Abstract
 Add to MetaCart
We present a data structure that allows to maintain in logarithmic time all partial sums of elements of a linear array during incremental changes of elementâ€™s values. Key words: Partial sums; Data structures; Algorithms 1
An algorithm for finding best matches in logarithmic expected time
 ACM Transactions on Mathematical Software
, 1977
"... An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record. The computation required to organize the file is proportional to kNlogN. The expected number of recor ..."
Abstract

Cited by 759 (2 self)
 Add to MetaCart
An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record. The computation required to organize the file is proportional to kNlogN. The expected number of records examined in each search is independent of the file size. The expected computation to perform each search is proportionalto 1ogN. Empirical evidence suggests that except for very small files, this algorithm is considerably faster than other methods.
PolynomialTime Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
 SIAM J. on Computing
, 1997
"... A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. ..."
Abstract

Cited by 1268 (5 self)
 Add to MetaCart
A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration
Logarithmic Time Parallel Bayesian Inference
 Proc. 14th Conf. Uncertainty in Artificial Intelligence
, 1998
"... I present a parallel algorithm for exact probabilistic inference in Bayesian networks. For polytree networks with n variables, the worstcase time complexity is O(logn) on a CREW PRAM (concurrentread, exclusivewrite parallel randomaccess machine) with n processors, for any constant number of evide ..."
Abstract

Cited by 29 (0 self)
 Add to MetaCart
I present a parallel algorithm for exact probabilistic inference in Bayesian networks. For polytree networks with n variables, the worstcase time complexity is O(logn) on a CREW PRAM (concurrentread, exclusivewrite parallel randomaccess machine) with n processors, for any constant number
Algorithms for Quantum Computation: Discrete Logarithms and Factoring
, 1994
"... A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a increase in computation time of at most a polynomial factor. It is not clear whether this is still true when quantum mechanics is taken into consi ..."
Abstract

Cited by 1103 (7 self)
 Add to MetaCart
A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a increase in computation time of at most a polynomial factor. It is not clear whether this is still true when quantum mechanics is taken
Doubly Logarithmic Time Parallel Sorting
"... Recently, attempts have been made to separate the problem of parallel sorting from that of list ranking, in order to get around the well known\Omega\Gamma/33 n= log log n) lower bound. These approaches have been of two kinds  chain sorting and padded sorting. Here we present nearly optimal, comp ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
, comparison based padded sorting algorithms that run in average case time O( 1 ffl 2 + 1 ffl log log n) using n 1+ffl processors, and O(n 1+ffl ) space, on an Common CRCW PRAM.From these results, algorithms for chain sorting within the same time and processor bounds can be easily obtained. Using a
Circle Separability Queries in Logarithmic Time
"... In this paper we preprocess a set P of n points so that we can answer queries of the following form: Given a convex mgon Q, report the minimum circle containing P and excluding Q. Our data structure can be constructed in O(n log n) time using O(n) space, and answers queries in O(log n + log m) time ..."
Abstract
 Add to MetaCart
In this paper we preprocess a set P of n points so that we can answer queries of the following form: Given a convex mgon Q, report the minimum circle containing P and excluding Q. Our data structure can be constructed in O(n log n) time using O(n) space, and answers queries in O(log n + log m
Results 1  10
of
530,140