Swimming Meets Statistics

When experience meets language statistics :

Nachdiplom Lecture: Statistics Meets Optimization 7.1 Introduction

In previous lectures, we have analyzed random forms of optimization problems, in which the randomness was injected (via random projection) for algorithmic reasons. On the other hand, in statistical problems—even without considering approximations—the starting point is a random instance of an optimization problem. To be more concrete, suppose that we are interested in estimating some parameter θ...

Developmental origins of hypertension: biology meets statistics.

T he concept that environmental factors during development—both in utero and in early childhood—can permanently alter the adult phenotype derives from the seminal epidemiologic observations of Professor David Barker (1). He and his colleagues showed in the early 1990s that low birthweight predicted increased risk of cardiovascular diseases, including insulin resistance/diabetes (2–4), obesity (...

Nachdiplom Lecture: Statistics Meets Optimization Some Comments on Relative Costs

Directly solving the ordinary least squares problem will (in general) require O(nd) operations. From Table 5.1, the Gaussian sketch does not actually improve upon this scaling for unconstrained problems: when m d (as is needed in the unconstrained case), then computing the sketch SA requires O(nd) operations as well. If we compute sketches using the JLT, then this cost is reduced to O(nd log(d)...

Metadata for Traveling Statistics - The World of Statistics Meets the Semantic Web

The paper is focusing on the requirements to metadata in a world where the Internet and the Web has become the dominant communication and dissemination medium for statistical information. Four important aspects of metadata, (finding, understanding, assessing and sharing) will be discussed in the light of this development. Special focus will be kept on the ideas and concepts of the semantic web ...