The selection problem of an optimal set sensors estimating the snapshot high-dimensional data is considered. objective functions based on various criteria design are adopted to greedy method: D-optimality, A-optimality, and E-optimality, which maximizes determinant, minimize trace inverse, maximize minimum eigenvalue Fisher information matrix, respectively. First, matrix derived depending numbe...

The target article provokes three comments and one more general criticism. First, the reason it is not surprising that "[the optimality heuristic] is used most systematically and successful

René Kager’s textbook is one of the first to cover Optimality Theory (OT), a declarative grammar framework that swiftly took over phonology after it was introduced by Prince, Smolensky, and McCarthy in 1993. OT reclaims traditional grammar’s ability to express surface generalizations (“syllables have onsets,” “no nasal+voiceless obstruent clusters”). Empirically, some surface generalizations ar...

In recent years, sequential optimality conditions are frequently used for convergence of iterative methods to solve nonlinear constrained optimization problems. The sequential optimality conditions do not require any of the constraint qualications. In this paper, We present the necessary sequential complementary approximate Karush Kuhn Tucker (CAKKT) condition for a point to be a solution of a ...

Optimality Theory catches on in linguistics, rst in phonology, then in syntax , and recently also at the semantics / pragmatics interface. In this paper we point at some parallels between principles employed in optimality the-oretic interpretation, and notions from the well-established eld of Game Theory. Optimality theoretic interpretation can be deened as what we call an \interpretation game"...

In this paper we analyse optimality of the stable fixed point of the double bracket equations. We introduce different types of optimality and prove local and global optimality results with respect to the Schatten p-norms.

Optimality functions define stationarity in nonlinear programming, semi-infinite optimization, and optimal control in some sense. In this paper, we consider optimality functions for stochastic programs with nonlinear, possibly nonconvex, expected value objective and constraint functions. We show that an optimality function directly relates to the difference in function values at a candidate poi...

In this paper we discuss the sensitive discount opti-mality for Markov decision processes. The n-discount optimality is a reened selective criterion, that is a generalization of the average optimality and the bias optimality. Our approach is based on the system of nested linear programs. In the last section we provide an algorithm for the computation of the Blackwell optimal policy. The n-disco...