http://dx.doi.org/10.1016/j.anbehav.2015.11.022 0003-3472/© 2015 The Association for the Study of A Colonial species breed in densely aggregated territories containing no resources other than nest sites. This behaviour is usually explained by natural selection, for instance through benefits resulting from reduced predation risk. An alternative hypothesis suggests that, as in lek breeding system...

This paper studies several di erent plans for selecting coordinates for updating via Gibbs sampling. It exploits the inherent features of the Gibbs sampling formulation, most notably its neighborhood structure, to characterize and compare the plans with regard to convergence to equilibrium and variance of the sample mean. Some of the plans rely on completely or almost completely random coordina...

In this paper, we present a rigorous methodology for quantifying the anonymity provided by Tor against a variety of structural attacks, i.e., adversaries that compromise Tor nodes and thereby perform eavesdropping attacks to deanonymize Tor users. First, we provide an algorithmic approach for computing the anonymity impact of such structural attacks against Tor. The algorithm is parametric in t...

We prove performance guarantees for Bayesian learning algorithms, in particular stochastic model selection, with the help of potential functions. Such a potential quantifies the current state of learning in the system, in a way that the expected error in the next step is bounded by the expected decrease of the potential. For Bayesian stochastic model selection, an appropriate potential function...

When confronted to a clustering problem, one has to choose which algorithm to run. Building a system that automatically chooses an algorithm for a given task is the algorithm selection problem. Unlike the well-studied task of classification, clustering algorithm selection cannot rely on labels to choose which algorithm to use. However, in the context of constraint-based clustering, we argue tha...

Genetic algorithms have been successfully applied in the area of software testing. The demand for automation of test case generation in object oriented software testing is increasing. Genetic algorithms are well applied in procedural software testing but a little has been done in testing of object oriented software. This paper discusses genetic algorithms that can automatically select an effici...

In this paper, we present a rigorous methodology for quantifying the anonymity provided by Tor against a variety of structural attacks, i.e., adversaries that corrupt Tor nodes and thereby perform eavesdropping attacks to deanonymize Tor users. First, we provide an algorithmic approach for computing the anonymity impact of such structural attacks against Tor. The algorithm is parametric in the ...

This paper describes the possibilities of variable selection in large-scale industrial systems. It introduces knowledge-based, data-based and model-based methods for this purpose. As an example, Case-Based Reasoning application for the evaluation of the web break sensitivity in a paper machine is introduced. The application uses Linguistic Equations approach and basic Fuzzy Logic. The indicator...

This paper studies the feature selection problem using a greedy least squares regression algorithm. We show that under a certain irrepresentable condition on the design matrix (but independent of the sparse target), the greedy algorithm can select features consistently when the sample size approaches in nity. The condition is identical to a corresponding condition for Lasso. Moreover, under a s...

A major theme of CS264 is to use theory to derive good guidance about which algorithm to use to solve a given problem in a given domain. For most problems, there is no “one size fits all” algorithm, and the right algorithm to use depends on the set of inputs relevant for the application. In today’s lecture, we’ll turn this theme into a well-defined mathematical problem, formalized via statistic...