of small groups is examined. The problem of centrality The idea of centrality as applied to human communication was introduced by Bavelas in 1948. He was specifically concerned with communication in small groups and he hypothesized a relationship between structural centrality and influence in group

One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a low-dimensional manifold embedded in a high-dimensional space. Drawing

Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions

Ambiguity resolution is a central problem in language comprehension. Lexical and syntactic ambiguities are standardly assumed to involve different types of knowledge representations and be resolved by different mechanisms. An alternative account is provided in which both types of ambiguity derive

this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central

the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices according to each case

Entity authentication and key distribution are central cryptographic problems in distributed computing -- but up until now, they have lacked even a meaningful definition. One consequence is that incorrect and inefficient protocols have proliferated. This paper provides the first treatment

We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible

assumptions now standard within the Government-Binding (GB) framework. The central empirical problem addressed is the question of the proper analysis of the so-called "Poss-ing" gerund in English. This construction possesses simultaneously many properties of sentences, and many properties of noun

We consider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints- connectivity and biconnectivity, and one optimization objective