Probabilistic and Statistical Methods in Computer Science presents a large variety of applications of probability theory and statistics in computer science and more precisely in algorithm analysis, speech recognition and robotics. It is written on a self-contained basis: all probabilistic and statistical ...
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The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. 作者简介 ··· Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the...
They have applied their methods to identify known biologically relevant relationships and new genes that could potentially be novel biomarkers for cancer progression using a multi-platform dataset derived from patients with glioblastoma (an aggressive form of brain cancer). Jiang, Xue, Brufsky, Khan,...
In particular, probabilistic extensions of the loosely (resp., tightly) cou- pled dl Wenow recall the (loosely coupled) probabilistic dl-programs from [14]. We first define answer setsemantics of probabilistic dl-programs, and the notions of consistency and tight answers. Probabilistic data ...
Thus, the probabilistic approach has been widely applied in the areas of perception, motor control, and language, where the performance of dedicated computational modules vastly exceeds the abilities of any artificial computational methods by an enormous margin. Before turning to the main topics of ...
Proximity-ligation methods such as Hi-C allow us to map physical DNA–DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for iden
Doucet, A., de Freitas, J. F. G. & Gordon, N. J.Sequential Monte Carlo Methods in Practice(Springer, 2000). MATHGoogle Scholar Minka, T. P. Expectation propagation for approximate Bayesian inference. InProc. Uncertainty in Artificial Intelligence17362–369 (2001). ...
Application-level protocol specifications (i.e., how a protocol should behave) are helpful for network security management, including intrusion detection and intrusion prevention. The knowledge of protocol specifications is also an effective way of detecting malicious code. However, current methods for ...
The development of reliability-based design methods requires the use of general-purpose engineering analysis tools that predict the uncertainty in a response due to uncertainties in the model formulation and input parameters. Barriers that have prevented the full acceptance of probabilistic analysis methods...