In this paper various measures for the uniformity of distribution of a point set in the unit cube are studied. We show how the diaphony and spectral test based on Walsh functions appear naturally as the worst-case error of integration in certain Hilbert spaces which are based on Walsh functions. Furthermore, it has been shown that this worst-case error equals to the root mean square discrepancy...

Pairwise coverage of factors affecting software has been proposed to screen for potential errors. Techniques to generate test suites for pairwise coverage are evaluated according to many criteria. A small number of tests is a main criterion, as this dictates the time for test execution. Randomness has been exploited to search for small test suites, but variation occurs in the test suite produce...

We derive new margin-based inequalities for the probability of error of classifiers. The main feature of these bounds is that they can be calculated using the training data and therefore may be effectively used for model selection purposes. In particular, the bounds involve empirical complexities measured on the training data (such as the empirical fatshattering dimension) as opposed to their w...

We analyze the expected risk of linear classifiers for a fixed weight vector in the “minimax” setting. That is, we analyze the worst-case risk among all data distributions with a given mean and covariance. We provide a simpler proof of the tight polynomial-tail bound for general random variables. For sub-Gaussian random variables, we derive a novel tight exponentialtail bound. We also provide n...

Worst-case design is important whenever robustness to adverse environmental conditions must be ensured regardless of their probability. It leads to minimax optimization, which is most often treated assuming that prior knowledge makes the worst environmental conditions obvious, or that a closed-form expression for the performance index is available. This paper considers the important situation w...

Achieving accurate translation, especially in multiple domain documents with statistical machine translation systems, requires more and more bilingual texts and this need becomes more critical when training such systems for language pairs with scarce training data. In the recent years, there have been some researches on new sources of parallel texts that are documents which are not necessarily ...

We show that if M is a DFA with n states over an arbitrary alphabet and L = L(M), then the worst-case state complexity of L2 is n2 − 2n−1. If, however, M is a DFA over a unary alphabet, then the worst-case state complexity of L is kn− k + 1 for all k ≥ 2.

In the context of adolescents' subjective well-being (SWB), research has recently focused on a number of different school variables. The direction of the relationships between adolescents' SWB, academic achievement, and test anxiety is, however, still open although reciprocal causation has been hypothesized. The present study set out to investigate to what extent SWB, academic achievement, and ...

This paper presents an algorithm that reduces the cost of regression testing by reducing the number of test cases that must be re-run and by reducing the size of the program that they must be run on. The algorithm uses dependence graphs and program slicing to partition the components of the new program into two sets: preserved points—components that have unchanged run-time behavior; and affecte...

In this study, we paid attention to the reliability of phrase table. To make phrase table, We have been used Och’s method[3]. And this method sometimes generate completely wrong phrase table. We found that such phrase table caused by long parallel sentences. Therefore, we removed these long parallel sentences from training data. Also, we utilized general tools for statistical machine translatio...