C3nr02024j 9089..9100

Prediction from Partial Data, Renormalization, and Averaging

We summarize and compare our recent methods for reducing the complexity of computational problems, in particular dimensional reduction methods based on the Mori–Zwanzig formalism of statistical physics, block Monte-Carlo methods, and an averaging method for deriving an effective equation for a nonlinear wave propagation problem. We show that their common thread is scale change and renormalization.

An infinite-server queue influenced by a semi-Markovian environment

Responsibility for believing

1 Robert Adams argues against this assumption, providing counter-examples, in “Involuntary Sins,” Philosophical Review 94 (1985): 3–31. For a more recent argument against the assumption, see Angela M. Smith, “Responsibility for Attitudes: Activity and Passivity in Mental Life,” Ethics 115 (January 2005): 236–71. The assumption seems to appear in the opening of Book III of the Nicomachean Ethics...

Profinite Heyting Algebras

For a Heyting algebra A, we show that the following conditions are equivalent: (i) A is profinite; (ii) A is finitely approximable, complete, and completely joinprime generated; (iii) A is isomorphic to the Heyting algebra Up(X) of upsets of an image-finite poset X. We also show that A is isomorphic to its profinite completion iff A is finitely approximable, complete, and the kernel of every fi...

Interior-point methods for nonconvex nonlinear programming: regularization and warmstarts

In this paper, we investigate the use of an exact primal-dual penalty approach within the framework of an interior-point method for nonconvex nonlinear programming. This approach provides regularization and relaxation, which can aid in solving ill-behaved problems and in warmstarting the algorithm. We present details of our implementation within the loqo algorithm and provide extensive numerica...