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» A fast algorithm for computing large Fibonacci numbers
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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 3 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
158
Voted
PE
2011
Springer
167views Optimization» more  PE 2011»
14 years 10 months ago
Passage-time computation and aggregation strategies for large semi-Markov processes
High-level semi-Markov modelling paradigms such as semi-Markov stochastic Petri nets and process algebras are used to capture realistic performance models of computer and communic...
Marcel C. Guenther, Nicholas J. Dingle, Jeremy T. ...
CSC
2009
15 years 4 months ago
Fast Monte Carlo Algorithms on Re-Wired Small-World Spin Models
Small-world networks have become an important model for understanding many complex phenomena in science and in sociological contexts. One tool for exploring the critical and phase...
Kenneth A. Hawick
144
Voted
JSAC
2008
98views more  JSAC 2008»
15 years 3 months ago
Randomized consensus algorithms over large scale networks
Suppose we have a directed graph G with set of nodes V = {1, . . . , N} and a measure xi for every node i V . The average consensus problem consists in computing the average xA = ...
Fabio Fagnani, Sandro Zampieri
143
Voted
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
16 years 3 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry