We propose a Dynamic Face Recognition Committee Machine (DFRCM) consisting of five well-known state-of-the-art algorithms in this paper. In previous work, we have developed a static committee machine which outperforms all the individual algorithms in the experiments. However, the weight for each expert in the committee is fixed and cannot be changed once the system is trained. We propose a dyna...

We study a fully-connected parity machine with K hidden units for continuous weights. The geometrical structure of the weight space of this model is analyzed in terms of the volumes associated with the internal representations of training set. By examining the asymptotic behavior of order parameters in the large K limit, we nd the maximum number c , the storage capacity, of patterns per input u...

Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many problems, its performance can deteriorate in the presence of patterns with incorrect labels. In this work we shall use parallel perceptrons (PP), a novel approach to the classical committee machines, to detect whether ...

J. Hertz Nordita Blegdamsvej 17 2100 Copenhagen 0 Denmark The problem of learning from examples in multilayer networks is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error of a fully connected committee machine in the limit of a large number of hidden units. If the number of training examples is proportional to the n...

In this paper, we propose a heterogeneous committee machine for face processing including face detection and recognition. Our proposed system consists of two components, Face Detection Committee Machine (FDCM) and Face Recognition Committee Machine (FRCM), which employs three and five well-known state-of-the-art approaches respectively. We engage different methodologies to solve the face detect...

Permeability prediction problem has been examined using several methods such as empirical formulas, regression analysis and intelligent systems especially neural networks and fuzzy logic. This study proposes an improved and novel model for predicting permeability from conventional well log data. The methodology is integration of empirical formulas, multiple regression and neuro-fuzzy in a commi...

We study generalization in a committee machine with non{overlapping receptive elds trained to implement a function of the same structure. Using the replica method, we calculate the generalization error in the limit of a large number of hidden units. For continuous weights the generalization error falls oo asymptotically inversely proportional to , the number of training examples per weight. For...