We prove a result concerning objective functions that can be used to obtain eÆcient and balanced solutions to the multi-commodity network ow problem. This type of solution is of interest when routing traÆc in the Internet. A particular case of the result proved here (see Corollary 2 below) was stated without proof in a previous paper. Objective Functions for Balance in TraÆc Engineering? Juan A...

-Fixed-outline floorplanning enables multilevel hierarchical design, where aspect ratios and area of floorplans are usually imposed by higher level floorplanning and must be satisfied. Simulated Annealing is widely used in the floorplanning problem. It is well-known that the solution space, solution perturbation, and objective function are very important for Simulated Annealing. In this paper, ...

Introduction: Science A computer scientist seems an odd choice to speak either about science in the forest, or science in the past. Computer science is more often located in cities and offices than in forests, and is concerned with the challenges of the future rather than the past. ‘Science’ appears to be a point of enquiry shared with this symposium, but even this word is open to debate. It is...

One of the most important stages in data preprocessing for data mining is feature selection. Real-world data analysis, data mining, classification and modeling problems usually involve a large number of candidate inputs or features. Less relevant or highly correlated features decrease, in general, the classification accuracy, and enlarge the complexity of the classifier. Feature selection is a ...

A new approach to clustering multivariate data, based on a multi-level linear mixed model, is proposed. A key feature of the model is that observations from the same cluster are correlated, because they share cluster specific random effects. The inclusion of cluster specific random effects allows parsimonious departure from an assumed base model for cluster mean profiles. This departure is capt...

MOTIVATION A critical component of in silico analysis of underdetermined metabolic systems is the identification of the appropriate objective function. A common assumption is that the objective of the cell is to maximize growth. This objective function has been shown to be consistent in a few limited experimental cases, but may not be universally appropriate. Here a method is presented to quant...

Context-free inference is a standard part of many NLP pipelines. Most approaches use a variant of the CYK dynamic programming algorithm to populate a chart structure with predicted nonterminals over each span. We can extract a parse tree from this chart in several ways. In this work, we compare two commonly-used decoding approaches (Viterbi and max-rule) with a minimum-bayes-risk (MBR) method w...

This paper develops tools for analyzing properties of stochastic objective functions that take the form ( , ) ( , ) ( ; ) V u dF ≡ ∫s x x s s θ θ . The paper analyzes the relationship between properties of the primitive functions, such as the utility functions u and probability distributions F, and properties of the stochastic objective. The methods are designed to address problems where the ut...

Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure. However, in the statistical setting where we assume that the finite data set has been sampled from some underlying space, the goal is not to find the best partition of the given sample, but to approximate the true part...

We introduce a parameterized version of set cover that generalizes several previously studied problems. Given a ground set V and a collection of subsets Si of V , a feasible solution is a partition of V such that each subset of the partition is included in one of the Si. The problem involves maximizing the mean subset size of the partition, where the mean is the generalized mean of parameter p,...