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
S.R. Dorling
  • ESANN 2002 - Heteroscedastic regularised kernel regression for prediction of episodes of poor air quality [Details]
  • ESANN 2003 - Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression [Details]
Daniel Dornbusch
  • ESANN 2010 - Finding correlations in multimodal data using decomposition approaches [Details]
José R. Dorronsoro
  • ESANN 2020 - Visualization of the Feature Space of Neural Networks [Details]
  • ESANN 2026 - Kernel Thinning for faster KSVM hyper-parametrization [Details]
José R. Dorronsoro
  • ESANN 2010 - Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs [Details]
  • ESANN 2014 - Sparse one hidden layer MLPs [Details]
  • ESANN 2015 - Diffusion Maps parameters selection based on neighbourhood preservation [Details]
  • ESANN 2015 - Solving constrained Lasso and Elastic Net using nu-SVMs [Details]
  • ESANN 2016 - Auto-adaptive Laplacian Pyramids [Details]
  • ESANN 2018 - Revisiting FISTA for Lasso: Acceleration Strategies Over The Regularization Path [Details]
José Dorronsoro
  • ESANN 2008 - An accelerated MDM algorithm for SVM training [Details]
  • ESANN 2009 - Rosen's projection method for SVM training [Details]
J.R. Dorronsoro
  • ESANN 2011 - Sparse LS-SVMs with L0–norm minimization [Details]
Lucas H. dos Santos
  • ESANN 2026 - Non-Linear Activation Functions for Deep Riemannian Neural Networks [Details]
Priscila G.M. dos Santos
  • ESANN 2019 - A WNN model based on Probabilistic Quantum Memories [Details]
Gerson H. dos Santos
  • ESANN 2015 - The use of RBF neural network to predict building’s corners hygrothermal behavior [Details]
Leandro dos Santos Coelho
  • ESANN 2018 - Cheetah Based Optimization Algorithm: A Novel Swarm Intelligence Paradigm [Details]
  • ESANN 2018 - Meerkats-inspired Algorithm for Global Optimization Problems [Details]
  • ESANN 2018 - Radar Based Pedestrian Detection using Support Vector Machine and the Micro Doppler Effect [Details]
Bernd Doser
  • ESANN 2016 - Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs [Details]
Rodney Douglas
  • ESANN 2004 - A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses [Details]
Stella Douka
  • ESANN 2025 - Growth strategies for arbitrary DAG neural architectures [Details]
Sylvain Douté
  • ESANN 2008 - Inverting hyperspectral images with Gaussian Regularized Sliced Inverse Regression [Details]
  • ESANN 2009 - Support vectors machines regression for estimation of mars surface physical properties [Details]
Kenji Doya
  • ESANN 2010 - Free-energy-based reinforcement learning in a partially observable environment [Details]
B. Doyon
  • ESANN 1999 - Mean-field equations reveal synchronization in a 2-populations neural network model [Details]
Dimitris Dracopoulos
  • ESANN 2014 - Application of Newton's Method to action selection in continuous state- and action-space reinforcement learning [Details]
Mauro Dragone
  • ESANN 2016 - RSS-based Robot Localization in Critical Environments using Reservoir Computing [Details]
Aldo Franco Dragoni
  • ESANN 2010 - Modeling contextualized textual knowledge as a Long-Term Working Memory [Details]
Pier Luigi Dragotti
  • ESANN 2017 - Solving Inverse Source Problems for Sources with Arbitrary Shapes using Sensor Networks [Details]
Noémie Draguet
  • ESANN 2025 - Making Convolutional Neural Networks Energy-Efficient: An Introduction [Details]
J.A. Drakopoulos
  • ESANN 1995 - Multi-sigmoidal units and neural networks [Details]
Matthew Draper
  • ESANN 2005 - performance of EMI based mine detection using back-propagation neural networks [Details]
J.P. Draye
  • ESANN 1993 - An efficient learning model for the neural integrator of the oculomotor system [Details]
  • ESANN 1997 - Evidence of efficiency of recurrent neural networks with ARMA-like units [Details]
J.-P. Draye
  • ESANN 1995 - Active noise control with dynamic recurrent neural networks [Details]
  • ESANN 1995 - Identification of the human arm kinetics using dynamic recurrent neural networks [Details]
  • ESANN 1996 - Adaptative time constants improve the dynamic features of recurrent neural networks [Details]
  • ESANN 1996 - Negative initial weights improve learning in recurrent neural networks [Details]
  • ESANN 1998 - Control of a subsonic electropneumatic acoustic generator with dynamic recurrent neural networks [Details]
Philippe Dreesen
  • ESANN 2012 - Joint Regression and Linear Combination of Time Series for Optimal Prediction [Details]
  • ESANN 2012 - Weighted/Structured Total Least Squares problems and polynomial system solving [Details]
  • ESANN 2012 - maximum likelihood estimation and polynomial system solving [Details]
E. Drege
  • ESANN 1998 - Face recognition: pre-processing techniques for linear autoassociators [Details]
P. Drezet
  • ESANN 1999 - An efficient formulation of sparsity controlled support vector regression [Details]
Fabrice Druaux
  • ESANN 2009 - Self-organising map for large scale processes monitoring [Details]
F. Druaux
  • ESANN 2003 - Autonomous learning algorithm for fully connected recurrent networks [Details]