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The Nobel Prize-winning Ameconomistonomist Harry M. Markowitz provided a boost for nonlinear optimization in 1958 when he formulated the problem of finding an efficient investment portfolio as a nonlinear optimization problem with a quadratic objective function.
Khan and Pop [19, 20] formulated the problem of laminar boundary-layer flow of a nanofluid past a stretching sheet.
Motivated by these facts, we formulated the problem of virtual screening from high-throughput screening assays as a multi-label classification problem.
Wu et al. [18] formulated the problem of surface normal recovery as a rank minimization problem, which can be solved via convex optimization.
In this paper, we have formulated the problem of steering the opinion of a group of individuals as a containment control problem.
Authors in [17] have formulated the problem of jamming in CR networks with primary users as a zero-sum stochastic game, where channel hopping was considered as the anti-jamming scheme and minimax-Q as the learning algorithm.
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We formulate the problem of filtering targeted and non-targeted malicious e-mails as a Stackelberg security game.
Markov Random Field (MRF) model formulates the problem of dense matching as a Bayes decision task.
We formulate the problem of finding corresponding landmarks as a minimization of an objective function comprised of two entropy-based terms.
Formulating the problem of face recognition under the emerging theory of compressed sensing, we examine the role of feature selection/dimensionality reduction from the perspective of sparse representation.
A similar approach is very popular in optimization where everyone knows that one should try very hard to formulate the problem of interest as a convex program.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com