In Rn, every vector can be written as a (unique) linear combination of the standard basis e1,..., en. A notion weaker than a basis is a spanning set: a set of vectors spans Rn if their linear combinations fill up the whole space. The difference between a spanning set and a basis is simply that a

of semantic description, where the semantic load is spread more evenly throughout the lexicon. I argue that lexical decomposition is possible if it is performed generatively. Rather than assuming a fixed set of primitives, I will assume a fixed number of generative devices that can be seen as constructing

Generative communication is the basis of a new distributed programming langauge that is intended for systems programming in distributed settings generally and on integrated network computers in particular. It differs from previous interprocess communication models in specifying that messages

details about the internals of the tools and how to customize them. With this guide, the tool set can be brought up and generating results in under an hour (on supported platforms). 1

clustering algorithm called CURE that is more robust to outliers, and identifies clusters having non-spherical shapes and wide variances in size. CURE achieves this by representing each cluster by a certain fixed number of points that are generated by selecting well scattered points from the cluster

distributions corresponding to hyperellipsoids with high axis ratio. In simulations, the generating set adaptation is compared to two other schemes which also can produce non axisparallel mutation ellipsoids. It turns out to be the only adaptation scheme which is completely independent of the chosen

We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel

ltaic (PV) electricity production from an intermittent Since 1978, compressed air energy storage (CAES) compressed air can then be released on demand to the CAES plant’s turbo-generator set to generate premium value electricity. The first CAES plant was built in broadened in the ittency of wind g

workload generation tool which mimics a set of real users accessing a server. The tool, called Surge (Scalable URL Reference Generator) generates references matching empirical measurements of 1) server file size distribution; 2) request size distribution; 3) relative file popularity; 4) embedded file

We compare discriminative and generative learning as typified by logistic regression and naive Bayes. We show, contrary to a widely held belief that discriminative classifiers are almost always to be preferred, that there can often be two distinct regimes of performance as the training set size