2008 |
31 | EE | David Meunier,
Hélène Paugam-Moisy:
Neural networks for computational neuroscience.
ESANN 2008: 367-378 |
30 | EE | Hélène Paugam-Moisy,
Régis Martinez,
Samy Bengio:
Delay learning and polychronization for reservoir computing.
Neurocomputing 71(7-9): 1143-1158 (2008) |
2007 |
29 | EE | Hélène Paugam-Moisy,
Régis Martinez,
Samy Bengio:
A supervised learning approach based on STDP and polychronization in spiking neuron networks.
ESANN 2007: 427-432 |
2006 |
28 | EE | David Meunier,
Hélène Paugam-Moisy:
Cluster detection algorithm in neural networks.
ESANN 2006: 19-24 |
27 | EE | Sylvain Chevallier,
Philippe Tarroux,
Hélène Paugam-Moisy:
Saliency extraction with a distributed spiking neural network.
ESANN 2006: 209-214 |
26 | EE | Anthony Mouraud,
Hélène Paugam-Moisy:
Learning and discrimination through STDP in a top-down modulated associative memory.
ESANN 2006: 611-616 |
25 | | Anthony Mouraud,
Hélène Paugam-Moisy,
Didier Puzenat:
A Distributed and Multithreaded Neural Event Driven Simulation Framework.
Parallel and Distributed Computing and Networks 2006: 212-217 |
24 | EE | Anthony Mouraud,
Hélène Paugam-Moisy:
Learning and discrimination through STDP in a top-down modulated associative memory
CoRR abs/cs/0611104: (2006) |
2005 |
23 | | Sylvain Chevallier,
Hélène Paugam-Moisy,
François Lemaître:
Distributed Processing for Modelling Real-Time Multimodal Perception in a Virtual Robot.
Parallel and Distributed Computing and Networks 2005: 393-398 |
22 | EE | Anthony Mouraud,
Didier Puzenat,
Hélène Paugam-Moisy:
DAMNED: A Distributed and Multithreaded Neural Event-Driven simulation framework
CoRR abs/cs/0512018: (2005) |
21 | EE | David Meunier,
Hélène Paugam-Moisy:
Simulation d'un amorçage intermodal sur un réseau de neurones impulsionnels.
Revue d'Intelligence Artificielle 19(1-2): 375-388 (2005) |
2004 |
20 | | David Meunier,
Hélène Paugam-Moisy:
A "spiking" bidirectional associative memory for modeling intermodal priming.
Neural Networks and Computational Intelligence 2004: 25-30 |
19 | EE | Yann Guermeur,
Gianluca Pollastri,
André Elisseeff,
Dominique Zelus,
Hélène Paugam-Moisy,
Pierre Baldi:
Combining protein secondary structure prediction models with ensemble methods of optimal complexity.
Neurocomputing 56: 305-327 (2004) |
2002 |
18 | | Hélène Paugam-Moisy,
Didier Puzenat,
Emanuelle Reynaud,
Jean-Philippe Magué:
Neural networks for modelling memory : case studies.
ESANN 2002: 71-82 |
17 | | Pablo A. Estévez,
Hélène Paugam-Moisy,
Didier Puzenat,
Manuel Ugarte:
A scalable parallel algorithm for training a hierarchical mixture of neural experts.
Parallel Computing 28(6): 861-891 (2002) |
2001 |
16 | EE | Olivier Teytaud,
Hélène Paugam-Moisy:
Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms.
ICANN 2001: 265-270 |
2000 |
15 | EE | Hélène Paugam-Moisy,
André Elisseeff,
Yann Guermeur:
Generalization Performance of Multiclass Discriminant Models.
IJCNN (4) 2000: 177-182 |
14 | EE | Yann Guermeur,
André Elisseeff,
Hélène Paugam-Moisy:
A New Multi-Class SVM Based on a Uniform Convergence Result.
IJCNN (4) 2000: 183-188 |
1999 |
13 | | Cédric Bertolini,
Hélène Paugam-Moisy,
Didier Puzenat:
Priming an Artificial Associative Memory.
IWANN (1) 1999: 348-356 |
12 | EE | André Elisseeff,
Hélène Paugam-Moisy:
JNN, a randomized algorithm for training multilayer networks in polynomial time.
Neurocomputing 29(1-3): 3-24 (1999) |
1998 |
11 | | Claire Kenyon,
Hélène Paugam-Moisy:
Multilayer Neural Networks and Polyhedral Dichotomies.
Ann. Math. Artif. Intell. 24(1-4): 115-128 (1998) |
1996 |
10 | | V. Demian,
Frederic Desprez,
Hélène Paugam-Moisy,
Makan Pourzandi:
Parallel Implementation of RBF Neural Networks.
Euro-Par, Vol. II 1996: 243-250 |
9 | EE | G. Brightwell,
Claire Kenyon,
Hélène Paugam-Moisy:
Multilayer Neural Networks: One or Two Hidden Layers?
NIPS 1996: 148-154 |
8 | EE | André Elisseeff,
Hélène Paugam-Moisy:
Size of Multilayer Networks for Exact Learning: Analytic Approach.
NIPS 1996: 162-168 |
1995 |
7 | EE | Bernard Girau,
Hélène Paugam-Moisy:
Load sharing in the training set partition algorithm for parallel neural learning.
IPPS 1995: 586-591 |
1994 |
6 | | Arnulfo P. Azcarraga,
Hélène Paugam-Moisy,
Didier Puzenat:
A Incremental Neural Classifier on a MIMD Parallel Computer.
Applications in Parallel and Distributed Computing 1994: 13-22 |
5 | | D. Girard,
Hélène Paugam-Moisy:
Strategies of Weight Updating for Parallel Back-propagation.
Applications in Parallel and Distributed Computing 1994: 335-336 |
4 | EE | Michel Cosnard,
Pascal Koiran,
Hélène Paugam-Moisy:
Bounds on the Number of Units for Computing Arbitrary Dichotomies by Multilayer Perceptrons.
J. Complexity 10(1): 57-63 (1994) |
1992 |
3 | | Hélène Paugam-Moisy:
Optimal Speedup Conditions for a Parallel Back-Propagation Algorithm.
CONPAR 1992: 719-724 |
2 | | S. Amghar,
Hélène Paugam-Moisy,
J. P. Royet:
Learning Methods for Odor Recognition Modeling.
IPMU 1992: 361-367 |
1 | | Michel Cosnard,
Pascal Koiran,
Hélène Paugam-Moisy:
Complexity Issues in Neural Network Computations.
LATIN 1992: 530-543 |