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NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 12 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
14 years 1 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
13 years 11 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
13 years 9 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
12 years 5 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