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
Xavier Domont
  • ESANN 2007 - A hierarchical model for syllable recognition [Details]
N. Donckers
  • ESANN 1999 - Extraction of intrinsic dimension using CCA - Application to blind sources separation [Details]
  • ESANN 2000 - A robust non-linear projection method [Details]
Nicolas Donckers
  • ESANN 2004 - HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems [Details]
D.J. Done
  • ESANN 2002 - Connectionist models investigating representations formed in the sequential generation of characters [Details]
Shuyu Dong
  • ESANN 2017 - Learning sparse models of diffusive graph signals [Details]
  • ESANN 2019 - Preconditioned conjugate gradient algorithms for graph regularized matrix completion [Details]
Michele Donini
  • ESANN 2014 - Easy multiple kernel learning [Details]
  • ESANN 2015 - Feature and kernel learning [Details]
  • ESANN 2016 - Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints [Details]
  • ESANN 2016 - Measuring the Expressivity of Graph Kernels through the Rademacher Complexity [Details]
  • ESANN 2017 - Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning [Details]
  • ESANN 2017 - Learning dot-product polynomials for multiclass problems [Details]
  • ESANN 2018 - Emerging trends in machine learning: beyond conventional methods and data [Details]
  • ESANN 2019 - PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors [Details]
Michele Donini
  • ESANN 2020 - Learning Deep Fair Graph Neural Networks [Details]
Benjamin Donnot
  • ESANN 2018 - Fast Power system security analysis with Guided Dropout [Details]
  • ESANN 2019 - LEAP nets for power grid perturbations [Details]
D. Donoho
  • ESANN 2002 - When does geodesic distance recover the true hidden parametrization of families of articulated images? [Details]
Balthazar Donon
  • ESANN 2019 - LEAP nets for power grid perturbations [Details]
Gauthier Doquire
  • ESANN 2011 - Mutual information based feature selection for mixed data [Details]
  • ESANN 2011 - Mutual information for feature selection with missing data [Details]
  • ESANN 2012 - On the Potential Inadequacy of Mutual Information for Feature Selection [Details]
  • ESANN 2013 - Risk Estimation and Feature Selection [Details]
B. Dorizzi
  • ESANN 1993 - MLP modular networks for multi-class recognition [Details]
S. R. Dorling
  • ESANN 2003 - Statistical downscaling with artificial neural networks [Details]
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 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]
J.R. Dorronsoro
  • ESANN 2011 - Sparse LS-SVMs with L0–norm minimization [Details]
José Dorronsoro
  • ESANN 2008 - An accelerated MDM algorithm for SVM training [Details]
  • ESANN 2009 - Rosen's projection method for SVM training [Details]
José R. Dorronsoro
  • ESANN 2020 - Visualization of the Feature Space of 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]