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Parallel retrieval of correlated patterns: From Hopfield networks to Boltzmann machines

Publications associées (32)

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Extended Hopfield Network for Sequence Learning: Application to Gesture Recognition

Aude Billard, Micha Hersch, André Maurer

In this paper, we extend the Hopfield Associative Memory for storing multiple sequences of varying duration. We apply the model for learning, recognizing and encoding a set of human gestures. We measure systematically the performance of the model against n ...

2005

Modeling Individual and Group Actions in Meetings: a Two-Layer HMM Framework

Daniel Gatica-Perez, Samy Bengio, Guillaume Lathoud, Dong Zhang

We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns, are inherently group-based (defined by the individual activities of meeting participa ...

2004

Modeling Individual and Group Actions in Meetings: a Two-Layer HMM Framework

Daniel Gatica-Perez, Samy Bengio, Guillaume Lathoud, Dong Zhang

IDIAP2004

Improving Face Authetication Using Virtual Samples

Sébastien Marcel, Samy Bengio, Norman Hoon Thian Poh

In this paper, we present a simple yet effective way to improve a face verification system by generating multiple virtual samples from the unique image corresponding to an access request. These images are generated using simple geometric transformations. T ...

2003

Levels of Dynamics and Adaptive Behavior in Evolutionary Neural Controllers

Dario Floreano, Jesper Blynel

Two classes of dynamical recurrent neural networks, Continuous Time Recurrent Neural Networks (CTRNNs) (Yamauchi and Beer, 1994) and Plastic Neural Networks (PNNs) (Floreano and Urzelai, 2000) are compared on two behavioral tasks aimed at exploring their c ...

2002

Improving Face Authetication Using Virtual Samples

Sébastien Marcel, Samy Bengio, Norman Hoon Thian Poh

IDIAP2002

A recurrent model for perceptual learning

Michael Herzog

Perceptual learning has received enhanced interest during the last years both from theoreticians and experimentalists. Recent experimental results reveal that mechanisms underlying perceptual learning are more complex than previously expected, thereby ruli ...

Optical Society of America1999

Channel networks

Andrea Rinaldo

This review proceeds from Luna Leopold's and Ronald Shreve's lasting accomplishments dealing with the study of random-walk and topologically random channel networks. According to the random perspective, which has had a profound influence on the interpretat ...

1998

Optimization of high order perceptrons

Neural networks are widely applied in research and industry. However, their broader application is hampered by various technical details. Among these details are several training parameters and the choice of the topology of the network. The subject of this ...

École Polytechnique Fédérale de Lausanne1997

Optimization of high order perceptrons

EPFL1997