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...

Alan Mathison Turing (1912 1954) was an English mathematician, logician, cryptanalyst, and computer scientist. He was highly influential in the development of computer science, providing a formalisation of the concepts of "algorithm" and "computation" by way of the Turing machine. His work played a pivotal role in the creation of the modern computer science. Turing is widely considered to be th...

The goal of having computers automatically solve problems is central to artificial intelligence, machine learning, and the broad area encompassed by what Turing called ‘machine intelligence’ [384]. Machine learning pioneer Arthur Samuel, in his 1983 talk entitled ‘AI: Where It Has Been and Where It Is Going’ [337], stated that the main goal of the fields of machine learning and artificial intel...

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 ...

The classification of subjects' pathologies enables a rigorousness to be applied to the treatment of certain pathologies, as doctors on occasions play with so many variables that they can end up confusing some illnesses with others. Thanks to Machine Learning techniques applied to a health-record database, it is possible to make using our algorithm. hClass contains a non-linear classification o...

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...

The goal of getting computers to automatically solve problems is central to artificial intelligence, machine learning, and the broad area encompassed by what Turing called “machine intelligence” (Turing, 1948, 1950). In his talk entitled AI: Where It Has Been and Where It Is Going, machine learning pioneer Arthur Samuel stated the main goal of the fields of machine learning and artificial intel...

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...