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 | 2011 | |
|---|---|---|
| c27 |      | Ludovic Arnold, Sébastien Rebecchi, Sylvain Chevallier, Hélène Paugam-Moisy: An Introduction to Deep Learning. ESANN 2011 |
| 2010 | ||
| c26 | | Ludovic Arnold, Hélène Paugam-Moisy, Michèle Sebag: Unsupervised Layer-Wise Model Selection in Deep Neural Networks. ECAI 2010: 915-920 |
| c25 | | Anthony Mouraud, Alain Guillaume, Hélène Paugam-Moisy: The DAMNED Simulator for Implementing a Dynamic Model of the Network Controlling Saccadic Eye Movements. ICANN (1) 2010: 272-281 |
| c24 | | Sylvain Chevallier, Hélène Paugam-Moisy, Michèle Sebag: SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system. NIPS 2010: 379-387 |
| 2009 | ||
| c23 | | Régis Martinez, Hélène Paugam-Moisy: Algorithms for Structural and Dynamical Polychronous Groups Detection. ICANN (2) 2009: 75-84 |
| 2008 | ||
| j7 | | Hélène Paugam-Moisy, Régis Martinez, Samy Bengio: Delay learning and polychronization for reservoir computing. Neurocomputing 71(7-9): 1143-1158 (2008) |
| c22 | | David Meunier, Hélène Paugam-Moisy: Neural networks for computational neuroscience. ESANN 2008: 367-378 |
| 2007 | ||
| c21 | | 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 | ||
| c20 | | David Meunier, Hélène Paugam-Moisy: Cluster detection algorithm in neural networks. ESANN 2006: 19-24 |
| c19 | | Sylvain Chevallier, Philippe Tarroux, Hélène Paugam-Moisy: Saliency extraction with a distributed spiking neural network. ESANN 2006: 209-214 |
| c18 | | Anthony Mouraud, Hélène Paugam-Moisy: Learning and discrimination through STDP in a top-down modulated associative memory. ESANN 2006: 611-616 |
| c17 |  | 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 |
| i2 | | Anthony Mouraud, Hélène Paugam-Moisy: Learning and discrimination through STDP in a top-down modulated associative memory. CoRR abs/cs/0611104 (2006) |
| 2005 | ||
| j6 | | 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) |
| c16 | | 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 |
| i1 | | Anthony Mouraud, Didier Puzenat, Hélène Paugam-Moisy: DAMNED: A Distributed and Multithreaded Neural Event-Driven simulation framework. CoRR abs/cs/0512018 (2005) |
| 2004 | ||
| j5 | | 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) |
| c15 | | David Meunier, Hélène Paugam-Moisy: A "spiking" bidirectional associative memory for modeling intermodal priming. Neural Networks and Computational Intelligence 2004: 25-30 |
| 2002 | ||
| j4 | | 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) |
| c14 | | Hélène Paugam-Moisy, Didier Puzenat, Emanuelle Reynaud, Jean-Philippe Magué: Neural networks for modelling memory : case studies. ESANN 2002: 71-82 |
| 2001 | ||
| c13 | | Olivier Teytaud, Hélène Paugam-Moisy: Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms. ICANN 2001: 265-270 |
| 2000 | ||
| c12 | | Hélène Paugam-Moisy, André Elisseeff, Yann Guermeur: Generalization Performance of Multiclass Discriminant Models. IJCNN (4) 2000: 177-182 |
| c11 | | Yann Guermeur, André Elisseeff, Hélène Paugam-Moisy: A New Multi-Class SVM Based on a Uniform Convergence Result. IJCNN (4) 2000: 183-188 |
| 1999 | ||
| j3 | | André Elisseeff, Hélène Paugam-Moisy: JNN, a randomized algorithm for training multilayer networks in polynomial time. Neurocomputing 29(1-3): 3-24 (1999) |
| c10 | | Cédric Bertolini, Hélène Paugam-Moisy, Didier Puzenat: Priming an Artificial Associative Memory. IWANN (1) 1999: 348-356 |
| 1998 | ||
| j2 | | Claire Kenyon, Hélène Paugam-Moisy: Multilayer Neural Networks and Polyhedral Dichotomies. Ann. Math. Artif. Intell. 24(1-4): 115-128 (1998) |
| 1996 | ||
| c9 | | V. Demian, Frederic Desprez, Hélène Paugam-Moisy, Makan Pourzandi: Parallel Implementation of RBF Neural Networks. Euro-Par, Vol. II 1996: 243-250 |
| c8 | | Graham Brightwell, Claire Kenyon, Hélène Paugam-Moisy: Multilayer Neural Networks: One or Two Hidden Layers? NIPS 1996: 148-154 |
| c7 | | André Elisseeff, Hélène Paugam-Moisy: Size of Multilayer Networks for Exact Learning: Analytic Approach. NIPS 1996: 162-168 |
| 1995 | ||
| c6 | | Bernard Girau, Hélène Paugam-Moisy: Load sharing in the training set partition algorithm for parallel neural learning. IPPS 1995: 586-591 |
| 1994 | ||
| j1 | | 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) |
| c5 | | 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 |
| c4 | | D. Girard, Hélène Paugam-Moisy: Strategies of Weight Updating for Parallel Back-propagation. Applications in Parallel and Distributed Computing 1994: 335-336 |
| 1992 | ||
| c3 | | Hélène Paugam-Moisy: Optimal Speedup Conditions for a Parallel Back-Propagation Algorithm. CONPAR 1992: 719-724 |
| c2 | | S. Amghar, Hélène Paugam-Moisy, J. P. Royet: Learning Methods for Odor Recognition Modeling. IPMU 1992: 361-367 |
| c1 | | Michel Cosnard, Pascal Koiran, Hélène Paugam-Moisy: Complexity Issues in Neural Network Computations. LATIN 1992: 530-543 |
Colors in the list of coauthors
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