This paper will describe a method and a program (align) for aligning sentences based on a simple statistical model of character lengths. The program uses the fact that longer sentences in one language tend to be translated into longer sentences in the other language, and that shorter sentences tend

This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. Tests using Wall Street

if that initial choice is close to a good solution. We devised a method called “affinity propagation,” which takes as input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of exemplars and corresponding clusters gradually emerges

Abstract-Let {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a

A menu of paired lottery choices is structured so that the crossover point to the high-risk lottery can be used to infer the degree of risk aversion. With "normal " laboratory payoffs of several dollars, most subjects are risk averse and few are risk loving. Scaling up all payoffs

conserved developmental systems that read an (almost) universal language encoded in DNA base pairs. As such, life is arranged hierarchically with a foundation of discrete, unblendable units (codons, and, for the most part, genes) capable of combining to create increasingly complex and virtually limitless

an accuracy in excess of 99 % in a random selected set of 1000 sentence pairs that we checked by hand. We show that even without he benefit of anchor points the correlation between the lengths of aligned sentences i strong enough that we should expect o achieve an accuracy of between 96 % and 97%. Thus

We present techniques to prove termination and innermost termination of term rewriting systems automatically. In contrast to previous approaches, we do not compare left- and right-hand sides of rewrite rules, but introduce the notion of dependency pairs to compare left-hand sides with special

et al., 2004) from aligned tree-string pairs, and present two main extensions of their approach: first, instead of merely computing a single derivation that minimally explains a sentence pair, we construct a large number of derivations that include contextually richer rules, and account for multiple

that deals with this problem by specifying that certain procedures cause a conditioned stimulus (CS) to lose effectiveness; in particular, we argue that a CS will lose associability when its consequences are accurately predicted. In contrast to other current models, the effectiveness of the reinforcer