The even and odd cut polytopes
Discrete Mathematics
Optimization: algorithms and consistent approximations
Optimization: algorithms and consistent approximations
Regular Article: Binary Cumulants
Advances in Applied Mathematics
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
| Hi-index | 7.29 |
This manuscript details Bayesian methodology for "learning by example", with binary n-sequences encoding the objects under consideration. Priors prove influential; conformable priors are described. Laplace approximation of Bayes integrals yields posterior likelihoods for all n-sequences. This involves the optimization of a definite function over a convex domain--efficiently effectuated by the sequential application of the quadratic program.