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
CesareC Alippi
  • ESANN 2021 - Deep learning for graphs [Details]
Simon Alix
  • ESANN 2024 - Towards Contrail Mitigation through Robust and Frugal AI-Driven Data Exploitation [Details]
Hamid Allaoui
  • ESANN 2018 - Order Crossover for the Inventory Routing Problem [Details]
B. Allotta
  • ESANN 2003 - Comparison of traditional and neural systems for train speed estimation [Details]
Vinoo Alluri
  • ESANN 2013 - Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis [Details]
J. Almaraz
  • ESANN 1993 - Modelling biological learning from its generalization capacity [Details]
Jonas Almeida
  • No papers found
Leandro Almeida
  • ESANN 2007 - Automatically searching near-optimal artificial neural networks [Details]
Jonas Almeida
  • ESANN 2022 - Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine [Details]
Carlos Alonso
  • ESANN 2006 - Rotation-based ensembles of RBF networks [Details]
Felipe Alonso Atienza
  • ESANN 2006 - Bootstrap feature selection in support vector machines for ventricular fibrillation detection [Details]
Amparo Alonso Betanzos
  • ESANN 2024 - AI-based algorithm for intrusion detection on a real dataset [Details]
Amparo Alonso-Betanzos
  • ESANN 2020 - Do we need hundreds of classifiers or a good feature selection? [Details]
Amparo Alonso-Betanzos
  • ESANN 2004 - Shear strength prediction using dimensional analysis and functional networks [Details]
  • ESANN 2005 - a new wrapper method for feature subset selection [Details]
  • ESANN 2007 - Classification of computer intrusions using functional networks. A comparative study [Details]
  • ESANN 2008 - A Method for Time Series Prediction using a Combination of Linear Models [Details]
  • ESANN 2008 - A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis [Details]
  • ESANN 2011 - Statistical dependence measure for feature selection in microarray datasets [Details]
  • ESANN 2012 - One-class classifier based on extreme value statistics [Details]
  • ESANN 2013 - A distributed wrapper approach for feature selection [Details]
  • ESANN 2014 - Modeling consumption of contents and advertising in online newspapers [Details]
  • ESANN 2015 - Learning features on tear film lipid layer classification [Details]
  • ESANN 2015 - On the use of machine learning techniques for the analysis of spontaneous reactions in automated hearing assessment [Details]
  • ESANN 2016 - Data complexity measures for analyzing the effect of SMOTE over microarrays [Details]
  • ESANN 2016 - Machine learning for medical applications [Details]
  • ESANN 2016 - One-class classification algorithm based on convex hull [Details]
  • ESANN 2016 - Using a feature selection ensemble on DNA microarray datasets [Details]
  • ESANN 2017 - A distributed approach for classification using distance metrics [Details]
  • ESANN 2017 - Algorithmic challenges in big data analytics [Details]
  • ESANN 2017 - Mutual information for improving the efficiency of the SCH algorithm [Details]
  • ESANN 2017 - Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing [Details]
  • ESANN 2018 - Analysis of imputation bias for feature selection with missing data [Details]
Amparo Alonso-Betanzos
  • ESANN 2023 - Automated green machine learning for condition-based maintenance [Details]
  • ESANN 2023 - Green Machine Learning [Details]
A. Alonso-Betanzos
  • ESANN 2003 - Recursive Least Squares for an Entropy Regularized MSE Cost Function [Details]
  • ESANN 2003 - Self-organizing maps and functional networks for local dynamic modeling [Details]
A. Alonso-Betanzos,
  • ESANN 2003 - Accelerating the convergence speed of neural networks learning methods using least squares [Details]
Tayfun Alpay
  • ESANN 2018 - An analysis of subtask-dependency in robot command interpretation with dilated CNNs [Details]
  • ESANN 2018 - Surprisal-based activation in recurrent neural networks [Details]
René Alquézar Mancho
  • ESANN 2014 - Misclassification of class C G-protein-coupled receptors as a label noise problem [Details]
Pierre Alquier
  • ESANN 2017 - Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering [Details]
Nawal Alqurashi
  • ESANN 2024 - Decision fusion based multimodal hierarchical method for speech emotion recognition from audio and text [Details]
Stephen Alstrup
  • ESANN 2015 - High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study [Details]
  • ESANN 2019 - Detecting Ghostwriters in High Schools [Details]
Tomas Aluja
  • ESANN 2013 - Handling missing values in kernel methods with application to microbiology data [Details]
Juan Carlos Alvarado-Pérez
  • ESANN 2015 - Geometrical homotopy for data visualization [Details]
M.R. Alvarez
  • 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]
Diego Álvarez
  • ESANN 2024 - Human Activity Recognition from Thigh and Wrist Accelerometry [Details]
Juan Carlos Alvarez
  • ESANN 2024 - Human Activity Recognition from Thigh and Wrist Accelerometry [Details]
M. Alvarez
  • ESANN 1994 - Decoding functions for Kohonen maps [Details]
Stephanie Alvarez Fernandez
  • ESANN 2016 - An Immune-Inspired, Dependence-Based Approach to Blind Inversion of Wiener Systems [Details]
Diego Álvarez-Estévez
  • ESANN 2016 - Automatic detection of EEG arousals [Details]
  • ESANN 2017 - Outlining a simple and robust method for the automatic detection of EEG arousals [Details]