Hélène Paugam-Moisy

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

Coauthor Index

1	S. Amghar	[2]
2	Arnulfo P. Azcarraga	[6]
3	Pierre Baldi	[19]
4	Samy Bengio	[29] [30]
5	Cédric Bertolini	[13]
6	G. Brightwell	[9]
7	Sylvain Chevallier	[23] [27]
8	Michel Cosnard	[1] [4]
9	V. Demian	[10]
10	Frédéric Desprez (Frederic Desprez)	[10]
11	André Elisseeff	[8] [12] [14] [15] [19]
12	Pablo A. Estévez	[17]
13	D. Girard	[5]
14	Bernard Girau	[7]
15	Yann Guermeur	[14] [15] [19]
16	Pascal Koiran	[1] [4]
17	François Lemaître	[23]
18	Jean-Philippe Magué	[18]
19	Régis Martinez	[29] [30]
20	Claire Mathieu (Claire Kenyon, Claire Kenyon-Mathieu)	[9] [11]
21	David Meunier	[20] [21] [28] [31]
22	Anthony Mouraud	[22] [24] [25] [26]
23	Gianluca Pollastri	[19]
24	Makan Pourzandi	[10]
25	Didier Puzenat	[6] [13] [17] [18] [22] [25]
26	Emanuelle Reynaud	[18]
27	J. P. Royet	[2]
28	Philippe Tarroux	[27]
29	Olivier Teytaud	[16]
30	Manuel Ugarte	[17]
31	Dominique Zelus	[19]

Colors in the list of coauthors