Guillaume Latombe

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Predators impact prey populations not only by consuming individuals, but also by altering their behaviours. These nonlethal effects can influence food web properties as much as lethal effects. The mechanisms of nonlethal effects include chronic and temporary anti-predator behaviours, the nature of which depends on the spatial dynamics of predators and the(More)
Although stochastic context-free grammars (SCFG) appear promising for the recognition and threat assessment of complex radar emitters in radar electronic support (ES) systems, the computational requirements for learning their production rule probabilities can be onerous. The two most popular methods, the inside-outside (IO) algorithm and the Viterbi score(More)
The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the(More)
Although stochastic context-free grammars (SCFGs) appear promising for recognition of radar emitters, and for estimation of their level of threat in radar electronic support (ES) systems, well-known techniques for learning their production rule probabilities are computationally demanding, and cannot efficiently reflect changes in operational environments.(More)
Although Stochastic context-free grammars appear promising for recognition of radar emitters, and for estimation of their respective level of threat in radar electronic support systems, well-known techniques for learning their production rule probabilities are computationally demanding. In this paper, three fast incremental alternatives, called graphical EM(More)
A challenge in the design of SCFGs for some applications is the computation of the probability distributions associated with its production rules. The most popular methods for this task are by far the inside-outside (IO) algorithm, which maximizes the likelihood of a data set, and the Viterbi score (VS) algorithm, which maximizes the likelihood of its best(More)
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