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
Raphaël Langhendries
  • ESANN 2021 - Deep Learning Model for Context-Dependent Survival Analysis [Details]
Rocco Langone
  • ESANN 2015 - Ranking Overlap and Outlier Points in Data using Soft Kernel Spectral Clustering [Details]
  • ESANN 2016 - Clustering from two data sources using a kernel-based approach with weight coupling [Details]
  • ESANN 2016 - Fast in-memory spectral clustering using a fixed-size approach [Details]
Petr Lansky
  • ESANN 2012 - How regular is neuronal activity? [Details]
P. Lansky
  • ESANN 1994 - Stochastic model of odor intensity coding in first-order olfactory neurons [Details]
  • ESANN 1995 - Some new results on the coding of pheromone intensity in an olfactory sensory neuron [Details]
Anders Lansner
  • ESANN 2005 - Attractor neural networks with patchy connectivity [Details]
  • ESANN 2006 - Recognition of handwritten digits using sparse codes generated by local feature extraction methods [Details]
Anders Lansner
  • ESANN 2021 - Semi-supervised learning with Bayesian Confidence Propagation Neural Network [Details]
  • ESANN 2023 - Spiking neural networks with Hebbian plasticity for unsupervised representation learning [Details]
Leon Lantz
  • ESANN 2025 - Data-Density guided Reinforcement Learning [Details]
Jérôme Lapuyade-Lahorgue
  • ESANN 2011 - Nearest neighbors and correlation dimension for dimensionality estimation. Application to factor analysis of real biological time series data. [Details]
Sohaib Laraba
  • No papers found
Sohaib Laraba
  • ESANN 2022 - Semi-synthetic Data for Automatic Drone Shadow Detection [Details]
Corentin Larroche
  • ESANN 2021 - Anomalous Cluster Detection in Large Networks with Diffusion-Percolation Testing [Details]
Corentin Larroche
  • ESANN 2024 - Inductive lateral movement detection in enterprise computer networks [Details]
Martha Larson
  • ESANN 2023 - Exploring the Importance of Sign Language Phonology for a Deep Neural Network [Details]
Carole Lartizien
  • ESANN 2014 - Robust outlier detection with L0-SVDD [Details]
  • ESANN 2016 - Converting SVDD scores into probability estimates [Details]
Anthony Larue
  • ESANN 2012 - From neuronal cost-based metrics towards sparse coded signals classification [Details]
Cecilia Laschi
  • ESANN 2014 - Spiking AGREL [Details]
  • ESANN 2018 - Spatial pooling as feature selection method for object recognition [Details]
Pavel Laskov
  • ESANN 2004 - Using classification to determine the number of finger strokes on a multi-touch tactile device [Details]
Pierre Latouche
  • No papers found
Pierre Latouche
  • ESANN 2013 - Activity Date Estimation in Timestamped Interaction Networks [Details]
  • ESANN 2013 - Bayesian non parametric inference of discrete valued networks [Details]
  • ESANN 2015 - A State-Space Model for the Dynamic Random Subgraph Model [Details]
  • ESANN 2015 - Exact ICL maximization in a non-stationary time extension of latent block model for dynamic networks [Details]
  • ESANN 2015 - Graphs in machine learning. An introduction [Details]
Pierre Latouche
  • ESANN 2022 - Deep latent position model for node clustering in graphs [Details]
Steven Latré
  • ESANN 2020 - Language Grounded Task-Adaptation in Reinforcement Learning [Details]
Martin Lauer
  • ESANN 2007 - Reinforcement learning in a nutshell [Details]
Fabien Lauer
  • ESANN 2018 - A sharper bound on the Rademacher complexity of margin multi-category classifiers [Details]
Manuel Laufer
  • ESANN 2024 - AI-based Collimation Optimization for X-Ray Imaging using Time-of-Flight Cameras [Details]
  • ESANN 2025 - Investigating the Impact of Imbalanced Medical Data on the Performance of Self-Supervised Learning Approaches [Details]
Ivano Lauriola
  • 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 - The minimum effort maximum output principle applied to Multiple Kernel Learning [Details]
Ivano Lauriola
  • ESANN 2020 - Exploring the feature space of character-level embeddings [Details]
  • ESANN 2020 - Language processing in the era of deep learning [Details]
Ludwig Lausser
  • ESANN 2008 - Detecting zebra crossings utilizing AdaBoost [Details]
Steven Lauwereins
  • ESANN 2014 - Context- and cost-aware feature selection in ultra-low-power sensor interfaces [Details]
R. Lauwereins
  • ESANN 1994 - VLSI complexity reduction by piece-wise approximation of the sigmoid function [Details]
Sverre Lauwers
  • ESANN 2025 - Enhancing Computer Vision with Knowledge: a Rummikub Case Study [Details]