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
Gilles Peiffer
  • ESANN 2026 - Towards Understanding The Winner-Take-Most Behavior Of Neural Network Representations [Details]
Julien Peignon
  • ESANN 2026 - Time Series Forecasting in the Presence of Explosive Bubbles [Details]
Enrique Pelayo
  • ESANN 2011 - SO-VAT: Self-Organizing Visual Assessment of cluster Tendency for large data sets [Details]
  • ESANN 2012 - magnitude sensitive competitive learning [Details]
Kristiaan Pelckmans
  • ESANN 2004 - sparse LS-SVMs using additive regularization with a penalized validation criterion [Details]
  • ESANN 2007 - Convex optimization for the design of learning machines [Details]
  • ESANN 2008 - Survival SVM: a practical scalable algorithm [Details]
  • ESANN 2009 - Transductively Learning from Positive Examples Only [Details]
  • ESANN 2010 - On the use of a clinical kernel in survival analysis [Details]
Joris Pelemans
  • ESANN 2020 - On the long-term learning ability of LSTM LMs [Details]
Reynier Peletier
  • ESANN 2018 - Globular Cluster Detection in the Gaia Survey [Details]
Reynier Peletier
  • ESANN 2023 - Improved the locally aligned ant technique (LAAT) strategy to recover manifolds embedded in strong noise [Details]
  • ESANN 2025 - Adaptive Locally Aligned Ant Technique for Manifold Detection and Denoising [Details]
  • ESANN 2026 - Hub-Aware Hybrid Search: Accelerating the Locally Aligned Ant Technique [Details]
M. Pelillo
  • ESANN 1995 - An asymmetric associative memory model based on relaxation labeling processes [Details]
Lorenzo Pellegrini
  • ESANN 2021 - Continual Learning at the Edge: Real-Time Training on Smartphone Devices [Details]
Bruno Pelletier
  • ESANN 2004 - On fields of nonlinear regression models [Details]
Oscar J. Pellicer Valero
  • ESANN 2020 - Cost-free resolution enhancement in Convolutional Neural Networks for medical image segmentation [Details]
Mario Pellicoro
  • ESANN 2007 - Causality and communities in neural networks [Details]
Jaakko Peltonen
  • No papers found
Jaakko Peltonen
  • ESANN 2012 - Sparse Nonparametric Topic Model for Transfer Learning [Details]
Jaakko Peltonen
  • ESANN 2022 - Supervised dimensionality reduction technique accounting for soft classes [Details]
Diego Hernán Peluffo-Ordóñez
  • ESANN 2015 - Geometrical homotopy for data visualization [Details]
Diego Peluffo-Ordoñez
  • ESANN 2013 - Normalized cuts clustering with prior knowledge and a pre-clustering stage [Details]
  • ESANN 2013 - support vector machine-based aproach for multi-labelers problems [Details]
Diego H. Peluffo-Ordonez
  • ESANN 2014 - A multi-class extension for multi-labeler support vector machines [Details]
  • ESANN 2014 - Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction [Details]
  • ESANN 2014 - Optimal Data Projection for Kernel Spectral Clustering [Details]
  • ESANN 2014 - Recent methods for dimensionality reduction: A brief comparative analysis [Details]
Marian Pena
  • ESANN 2006 - Outlier identification with the Harmonic Topographic Mapping [Details]
N. Pendock
  • ESANN 1999 - A simple associative neural network for producing spatially homogenous spectral abundance interpretations of hyperspectral imagery [Details]
Manuel G. Penedo
  • 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]
Frédéric Pennerath
  • ESANN 2024 - Clarity: a Deep Ensemble for Visual Counterfactual Explanations [Details]
Federico Pennino
  • ESANN 2025 - Trajectory-Embedded Matryoshka Representation Learning for Enhanced Similarity Analysis [Details]
J.A. Peperstraete
  • ESANN 1994 - VLSI complexity reduction by piece-wise approximation of the sigmoid function [Details]
J. Peperstraete
  • ESANN 1993 - Efficient decomposition of comparison and its applications [Details]
Sérgio Pequito
  • ESANN 2021 - IF: Iterative Fractional Optimization [Details]
Sérgio Pequito
  • ESANN 2020 - Equilibrium Propagation for Complete Directed Neural Networks [Details]
Francisco Pereira
  • No papers found
Alvaro Pereira
  • ESANN 2024 - Transfer learning to minimize the predictive risk in clinical research [Details]
Francisco Pereira
  • ESANN 2022 - Predicting Test Execution Times with Asymmetric Random Forests [Details]