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- optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail...
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- problems. The style of the book is probably best described by the following quote from...
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- efficient SAT solver. Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant...
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- algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to cite ... applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography ... data. Many important applications in e.g. optimization, probability, financial economics and optimal control...
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- probably takes less time to compute than...
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- Skew-t. Build and manipulate probability distributions of the skew-normal family and some related...
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- prerequisite is an honest course in probability and statistics. Finally, let us note that...
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- assignment, or with some probability picks a variable at random. WalkSAT first picks a clause ... previously satisfied clauses becoming unsatisfied, with some probability of picking one of the variables...
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- Stan: A C++ Library for Probability and Sampling. Stan is a probabilistic programming language implementing...
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- module calculates performance measures including queue-length probabilities and waiting-time probabilities for basic queueing...
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- paper ”Numerical Computation of Multivariate Normal Probabilities”, in J. of Computational and Graphical Stat...
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- briefly ProbLog, focusses on computing the success probability of a given query, either exactly ... ProbLog2 allows the user to compute marginal probabilities of any number of ground atoms ... presence of evidence (in comparison, the succes probability setting of ProbLog1 corresponds to having...
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- useful in the summarization and estimation of probability distributions. This report contains details of Fortran...
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- describe our classes in terms of probability distribution or density functions, and the locally maximal ... posterior probability parameters. We rate our classifications with an approximate posterior probability of the distribution ... computational complexity of the joint probability, and our marginalization is w.r.t. a local maxima ... parameter space. This posterior probability rating allows direct comparison of alternate density functions that differ...
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- almost all starting points, i.e., with probability one. The essence of all such algorithms...