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NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 1 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
PODC
2006
ACM
15 years 3 months ago
Computing separable functions via gossip
Motivated by applications to sensor, peer-to-peer, and adhoc networks, we study the problem of computing functions of values at the nodes in a network in a totally distributed man...
Damon Mosk-Aoyama, Devavrat Shah
WG
1993
Springer
15 years 1 months ago
Dually Chordal Graphs
Recently in several papers, graphs with maximum neighborhood orderings were characterized and turned out to be algorithmically useful. This paper gives a unified framework for cha...
Andreas Brandstädt, Feodor F. Dragan, Victor ...
CCCG
2008
14 years 11 months ago
Competitive Search for Longest Empty Intervals
A problem arising in statistical data analysis and pattern recognition is to find a longest interval free of data points, given a set of data points in the unit interval. We use t...
Peter Damaschke

Publication
141views
13 years 7 months ago
Measures of Diversity for Populations and Distances Between Individuals with Highly Reorganizable Genomes
In this paper we address the problem of defining a measure of diversity for a population of individuals whose genome can be subjected to major reorganizations during the evolution...
Claudio Mattiussi, Markus Waibel, Dario Floreano