The generalized replica exchange method (gREM) is applied to simulate a solid-liquid phase change in an adapted Dzugutov model system. The idea of gREM is to incorporate the merit of sampling from a generalized ensemble into the replica exchange paradigm. The generalized ensemble weights are determined from effective temperatures tailored for this system, through an inverse mapping strategy. Th...

Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the tran...

A general formulation of discrete optimization is to maximize a given function f : D → R over a discrete (finite) domain D. In general, of course, this problem may require |D| probes to f . One approach to making optimization more tractable is to be satisfied with finding a local maximum, i.e., a point at which f attains a value larger than all “neighboring” points, for some definition of neigh...

Recent work by Bengio et al. (2013) proposes a sampling procedure for denoising autoencoders which involves learning the transition operator of a Markov chain. The transition operator is typically unimodal, which limits its capacity to model complex data. In order to perform efficient sampling from conditional distributions, we extend this work, both theoretically and algorithmically, to gated ...

Several allocation rules are examined for the problem of optimizing a response function for a set of Bernoulli populations, where the population means are assumed to have a strict unimodal structure. This problem arises in dose response settings in clinical trials. The designs are evaluated both on their eeciency in identifying a good population at the end of the experiment, and in their eecien...

Recent work by Bengio et al. (2013) proposes a sampling procedure for denoising autoencoders which involves learning the transition operator of a Markov chain. The transition operator is typically unimodal, which limits its capacity to model complex data. In order to perform efficient sampling from conditional distributions, we extend this work, both theoretically and algorithmically, to gated ...

The number of species coexisting in ecological communities must be a consequence of processes operating on both local and regional scales. Although a great deal of experimental work has been devoted to local causes of diversity, little is known about the effects of regional processes on local diversity and how they contribute to global diversity patterns in marine systems. We tested the effects...

This work is a continuation of our previous papers devoted to exploration of the regular search procedures efficiency in binary search spaces. Here we formulate the problem in a rather general form as a problem of optimization of an unimodal pseudoboolean function given implicitly and obtain analitical estimates of the expected time of a minimum point search for procedures of direct local searc...

In continuous black-box optimization, various stochastic local search techniques are often employed, with various remedies for fighting the premature convergence. This paper surveys recent developments in the field (the most important from the author’s perspective), analyzes the differences and similarities and proposes a taxonomy of these methods. Based on this taxonomy, a variety of novel, pr...