This paper addresses recognition of human activities with stochastic structure, characterized by variable spacetime arrangements of primitive actions, and conducted by a variable ...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...
Packet delay greatly influences the overall performance of network applications. It is therefore important to identify causes and location of delay performance degradation within ...
Francesco Lo Presti, Nick G. Duffield, Joseph Horo...
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...