Electronic proceedings author index

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
Ranjitha Prasad
  • ESANN 2020 - MultiMBNN: Matched and Balanced Causal Inference with Neural Networks [Details]
Gabriel Prat
  • ESANN 2016 - Instance and feature weighted k-nearest-neighbors algorithm [Details]
Bavishna Balagopal Praveen
  • ESANN 2012 - Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning [Details]
Frédéric Precioso
  • ESANN 2012 - Linear kernel combination using boosting [Details]
  • ESANN 2017 - Active learning strategy for CNN combining batchwise Dropout and Query-By-Committee [Details]
Cristian Preda
  • ESANN 2012 - Curves clustering with approximation of the density of functional random variables [Details]
M. Pregenzer
  • ESANN 1995 - Improvement of EEG classification with a subject-specific feature selection [Details]
Dumitru Bogdan Prelipcean
  • No papers found
Philippe Preux
  • ESANN 2007 - A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD [Details]
Roberto Prevete
  • ESANN 2019 - Explaining classification systems using sparse dictionaries [Details]
J.-C. Prévotet
  • ESANN 2002 - Hardware solutions for implementation of neural networks in High Energy Physics triggers [Details]
Jean-Christophe Prévotet
  • ESANN 2008 - Neural network hardware architecture for pattern recognition in the HESS2 project [Details]
Rodolphe Priam
  • No papers found
B. Prieto
  • ESANN 1998 - Separation of sources in a class of post-nonlinear mixtures [Details]
  • ESANN 2001 - A stochastic and competitive network for the separation of sources [Details]
A. Prieto
  • ESANN 1994 - A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control [Details]
  • ESANN 1998 - Separation of sources in a class of post-nonlinear mixtures [Details]
  • ESANN 1998 - What are the main factors involved in the design of a Radial Basis Function Network? [Details]
  • ESANN 2002 - Orthogonal transformations for optimal time series prediction [Details]
J. C. Principe
  • ESANN 2003 - Accelerating the convergence speed of neural networks learning methods using least squares [Details]
  • ESANN 2003 - Recursive Least Squares for an Entropy Regularized MSE Cost Function [Details]
Jose C. Principe
  • ESANN 2011 - Information theory related learning [Details]
  • ESANN 2011 - Statistical dependence measure for feature selection in microarray datasets [Details]
  • ESANN 2012 - One-class classifier based on extreme value statistics [Details]
Timothée Proix
  • ESANN 2013 - Fast online adaptivity with policy gradient: example of the BCI ``P300''-speller [Details]
Timo Pröscholdt
  • ESANN 2010 - On Finding Complementary Clusterings [Details]
P. Protzel
  • ESANN 1996 - FlexNet - A flexible neural network construction algorithm [Details]
Alexandre Proutiere
  • ESANN 2017 - Viral initialization for spectral clustering [Details]
Ricardo Prudêncio
  • ESANN 2014 - Fine-tuning of support vector machine parameters using racing algorithms [Details]
  • ESANN 2015 - I/S-Race: An iterative Multi-Objective Racing Algorithm for the SVM Parameter Selection Problem [Details]
Yann Prudent
  • ESANN 2005 - A new learning algorithm for incremental self-organizing maps [Details]
P.K. Psomas
  • ESANN 1995 - Alternative output representation schemes affect learning and generalization of back-propagation ANNs; a decision support application [Details]
Augusto Pucci
  • ESANN 2006 - A Cyclostationary Neural Network model for the prediction of the NO2 concentration [Details]
Vikram Pudi
  • ESANN 2012 - RNN Based Batch Mode Active Learning Framework [Details]
Raphaël Puget
  • ESANN 2020 - Time Series Prediction using Disentangled Latent Factors [Details]
Matthieu Puigt
  • ESANN 2006 - A time-scale correlation-based blind separation method applicable to correlated sources [Details]
  • ESANN 2014 - Enhanced NMF initialization using a physical model for pollution source apportionment [Details]
  • ESANN 2017 - Environmental signal processing: new trends and applications [Details]
C.G. Puntonet
  • ESANN 1998 - Separation of sources in a class of post-nonlinear mixtures [Details]
  • ESANN 2001 - A stochastic and competitive network for the separation of sources [Details]
  • ESANN 2001 - The synergy between multideme genetic algorithms and fuzzy systems [Details]
  • ESANN 2002 - Orthogonal transformations for optimal time series prediction [Details]
C. G. Puntonet
  • ESANN 2003 - Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation [Details]
Carlos G. Puntonet
  • ESANN 2004 - ON-LINE SUPPORT VECTOR MACHINES AND OPTIMIZATION STRATEGIES [Details]