This paper proposes new methods to answer approximate nearest neighbor queries on a set of n points in d-dimensional Euclidean space. For any xed constant d, a data structure with...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
We are building a knowledge base (KB) of published structural data on the 30s ribosomal subunit in prokaryotes. Our KB is distinguished by a standardized representation of biologi...
Russ B. Altman, Neil F. Abernethy, Richard O. Chen
Abstract. We consider data structures and algorithms for preprocessing a labelled list of length n so that, for any given indices i and j we can answer queries of the form: What is...
Prosenjit Bose, Evangelos Kranakis, Pat Morin, Yih...