Results 241 to 250 of about 5,859,765 (291)

Probabilistic-fuzzy clustering algorithm

2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005
Clustering algorithms divide up a data set into classes/clusters, where similar data objects are assigned to the same cluster. When the boundary between clusters is ill defined, which yields situations where the same data object belongs to more than one class. The notion of fuzzy clustering becomes relevant.
Samia Nefti, Mourad Oussalah 0002
openaire   +1 more source

The probabilistic analysis of a greedy satisfiability algorithm

Random Structures & Algorithms, 2002
AbstractOn input a random 3‐CNF formula of clauses‐to‐variables ratior3applies repeatedly the following simple heuristic: Set to True a literal that appears in the maximum number of clauses, irrespective of their size and the number of occurrences of the negation of the literal (ties are broken randomly; 1‐clauses when they appear get priority).
Alexis C. Kaporis, Lefteris M. Kirousis, Efthimios G. Lalas   +2 more
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A probabilistic algorithm for vertex connectivity of graphs

Information Processing Letters, 1982
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Becker, M., Degenhardt, W., Doenhardt, J., Hertel, S., Kaninke, G., Kerber, W., Mehlhorn, K., Näher, S., Rohnert, H., Winter, T.   +9 more
openaire   +3 more sources

Monitoring Temporal Properties of Stochastic Systems

International Conference on Verification, Model Checking and Abstract Interpretation, 2008
A. Sistla, A. Srinivas, Probabilistic Algorithms   +2 more
semanticscholar   +1 more source

A probabilistic extension for the DDA algorithm

Proceedings of International Conference on Neural Networks (ICNN'96), 2002
Many algorithms to train radial basis function (RBF) networks have already been proposed. Most of them, however, concentrate on building function approximators and only few specialized algorithms are known that concentrate on RBFs for classification. They are based on heuristics that focus on finding areas where relatively few (or no) conflicts occur ...
openaire   +1 more source

Probabilistic algorithms in group theory

2006
A finite group G is commonly presented by a set of elements which generate G. We argue that for algorithmic purposes a considerably better presentation for a fixed group G is given by random generator set for G: a set of random elements which generate G. We bound the expected number of random elements requied to generate a given group G.
openaire   +1 more source

Human-level concept learning through probabilistic program induction

Science, 2015
B. Lake, R. Salakhutdinov, J. Tenenbaum
semanticscholar   +1 more source

Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva

Int. J. Robotics Res., 2000
S. Thrun, M. Beetz, Maren Bennewitz, Wolfram Burgard, A. Cremers, F. Dellaert, D. Fox, D. Hähnel, Charles R. Rosenberg, N. Roy, Jamieson Schulte, D. Schulz   +11 more
semanticscholar   +1 more source

Probability and Computing: Randomized Algorithms and Probabilistic Analysis

, 2005
M. Mitzenmacher, E. Upfal
semanticscholar   +1 more source

Truss Decomposition of Probabilistic Graphs: Semantics and Algorithms

SIGMOD Conference, 2016
Xin Huang, Wei Lu, L. Lakshmanan
semanticscholar   +1 more source