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
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]
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]
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]
Andrea Proia
  • ESANN 2025 - Towards Streaming Land Use Classification of Images with Temporal Distribution Shifts [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]
Carlos G. Puntonet
  • ESANN 2004 - ON-LINE SUPPORT VECTOR MACHINES AND OPTIMIZATION STRATEGIES [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]
Tuomas Puoliväli
  • ESANN 2013 - Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis [Details]
J.M. Pupo
  • ESANN 2000 - Neurocontrol of a binary distillation column [Details]
James Pustejovsky
  • ESANN 2017 - Fine-grained event learning of human-object interaction with LSTM-CRF [Details]
Evgeny Putin
  • ESANN 2018 - Pollen grain recognition using convolutional neural network [Details]
Jari Puttonen
  • ESANN 2015 - Prediction of concrete carbonation depth using decision trees [Details]
Felix Putze
  • ESANN 2018 - behaviour-based working memory capacity classification using recurrent neural networks [Details]
Didier Puzenat
  • ESANN 2012 - Real time drunkenness analysis in a realistic car simulation [Details]
  • ESANN 2013 - Multi-user Blood Alcohol Content estimation in a realistic simulator using Artificial Neural Networks and Support Vector Machines [Details]
D. Puzenat
  • ESANN 2002 - Neural networks for modeling memory : case studies [Details]
Alexander Pysik
  • ESANN 2019 - Machine learning in research and development of new vaccines products: opportunities and challenges [Details]
Eduardo J. P\'aez
  • ESANN 2020 - Machine learning framework for control in classical and quantum domains [Details]