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We consider LDPC codes, transmission over the binary symmetric channel (BSC), and decoding using Gallager's algorithm A. For those ensembles whose threshold is determined by the behavior of the algorithm at the beginning of the decoding process we derive a ...
Boosting is a general method for training an ensemble of classifiers with a view to improving performance relative to that of a single classifier. While the original AdaBoost algorithm has been defined for classification tasks, the current work examines it ...
Cantilever-based detection of ultrasmall forces is of great interest for several applications such as magnetic resonance force miscroscopy (MRFM) where an ultrahigh sensitive cantilever is used to detect magnetic resonance in small ensembles of electron or ...
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper we attempt to train and combine the base classifiers using an adaptive policy. This policy is ...
Boosting is a general method for training an ensemble of classifiers with a view to improving performance relative to that of a single classifier. While the original AdaBoost algorithm has been defined for classification tasks, the current work examines it ...
The static and dynamical properties of heavy water have been studied at ambient conditions with extensive Car-Parrinello molecular-dynamics simulations in the canonical ensemble, with temperatures ranging between 325 and 400 K. Density-functional theory, p ...
The very low temperature properties of two pyrochlore compounds, Yb2Ti2O7 and Gd2Sn2O7, were investigated using an ensemble of microscopic and bulk techniques. In both compounds, a first order transition is evidenced, as well as spin dynamics persisting do ...
The purpose of this thesis is to show on explicit examples how various theoretical concepts, ranging from statistical mechanics to stochastic control and from traffic theory to queuing systems, can be transferred to transport processes, encountered in part ...
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of using an adaptive policy for training and combining the base classifiers is put ...
Information processing in neocortex can be very fast, indicating that neuronal ensembles faithfully transmit rapidly changing signals to each other. Apart from signal-to-noise issues, population codes are fundamentally constrained by the neuronal dynamics. ...