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.-C. Liao
  • ESANN 2000 - Fuzzy entropy-constrained competitive learning algorithm [Details]
G. Libert
  • ESANN 1993 - An efficient learning model for the neural integrator of the oculomotor system [Details]
  • 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 1997 - Evidence of efficiency of recurrent neural networks with ARMA-like units [Details]
Pieter Libin
  • ESANN 2019 - Deep hybrid approach for 3D plane segmentation [Details]
Jiao Licheng
  • ESANN 2005 - A ridgelet kernel regression model using genetic algorithm [Details]
  • ESANN 2005 - Radar target recognition using SVMs with a wrapper feature selection driven by immune clonal algorithm [Details]
Robert Lieck
  • ESANN 2015 - Discovering temporally extended features for reinforcement learning in domains with delayed causalities [Details]
Yannic Lieder
  • ESANN 2021 - Constraint optimization for Echo State Networks applied to satellite image forecasting [Details]
S. Liehr
  • ESANN 1999 - Hidden Markov gating for prediction of change points in switching dynamical systems [Details]
Wei Shiung Liew
  • ESANN 2020 - Self-Organizing Kernel-based Convolutional Echo State Network for Human Actions Recognition [Details]
Elia Liitiäinen
  • ESANN 2006 - EM-algorithm for training of state-space models with application to time series prediction [Details]
  • ESANN 2007 - Nearest Neighbor Distributions and Noise Variance Estimation [Details]
  • ESANN 2008 - Using the Delta Test for Variable Selection [Details]
Jefrey Lijffijt
  • ESANN 2016 - Informative data projections: a framework and two examples [Details]
Konstantin K. Likharev
  • ESANN 2004 - Architectures for Nanoelectronic Neural Networks: New Results [Details]
Mariana Lilley
  • ESANN 2023 - On Instance Weighted Clustering Ensembles [Details]
D. Lim
  • ESANN 1998 - On the robust design of uncoupled CNNs [Details]
Ye-Sheen Lim
  • ESANN 2018 - Reinforcement Learning for High-Frequency Market Making [Details]
Sungwoo Lim
  • ESANN 2006 - Freeform surface induction from projected planar curves via neural networks [Details]
Priscila Lima
  • ESANN 2022 - A WiSARD-based conditional branch predictor [Details]
  • ESANN 2022 - Distributive Thermometer: A New Unary Encoding for Weightless Neural Networks [Details]
  • ESANN 2022 - Pruning Weightless Neural Networks [Details]
  • ESANN 2023 - Sun Tracking using a Weightless Q-Learning Neural Network [Details]
  • ESANN 2023 - WiSARD-based Ensemble Learning [Details]
João J. G. Lima
  • ESANN 2024 - Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models [Details]
Priscila Lima
  • ESANN 2009 - A brief introduction to Weightless Neural Systems [Details]
  • ESANN 2009 - Extracting fuzzy rules from “mental” images generated by a modified WISARD perceptron [Details]
  • ESANN 2012 - Recognition of HIV-1 subtypes and antiretroviral drug resistance using weightless neural networks [Details]
  • ESANN 2013 - B-bleaching: Agile Overtraining Avoidance in the WiSARD Weightless Neural Classifier [Details]
  • ESANN 2013 - WIPS: the WiSARD Indoor Positioning System [Details]
  • ESANN 2015 - A WiSARD-based multi-term memory framework for online tracking of objects [Details]
  • ESANN 2016 - Semi-Supervised Classification of Social Textual Data Using WiSARD [Details]
  • ESANN 2017 - Automatic crime report classi cation through a weightless neural network [Details]
  • ESANN 2018 - Near-optimal facial emotion classification using a WiSARD-based weightless system [Details]
Priscila Lima
  • ESANN 2020 - Detection of elementary particles with the WiSARD n-tuple classifier [Details]
  • ESANN 2020 - Fast Deep Neural Networks Convergence using a Weightless Neural Model [Details]
  • ESANN 2020 - Interpretation of Model Agnostic Classifiers via Local Mental Images [Details]
  • ESANN 2021 - A bag of nodes primer on weightless graph classification [Details]
  • ESANN 2021 - Functional Gradient Descent for n-Tuple Regression [Details]
Priscila M. V. Lima Lima
  • ESANN 2011 - Clustering data streams with weightless neural networks [Details]
Priscila Lima
  • No papers found
Rafael Lima de Carvalho
  • ESANN 2014 - Online tracking of multiple objects using WiSARD [Details]
Aluizio Lima Filho
  • ESANN 2019 - Prediction of palm oil production with an enhanced n-Tuple Regression Network [Details]
Aluizio Lima Filho
  • ESANN 2020 - Interpretation of Model Agnostic Classifiers via Local Mental Images [Details]
Christian Limberg
  • ESANN 2018 - Efficient accuracy estimation for instance-based incremental active learning [Details]
Abdelhakim Limem
  • ESANN 2014 - Enhanced NMF initialization using a physical model for pollution source apportionment [Details]
Mu-Han Lin
  • ESANN 2019 - Application of deep neural networks for automatic planning in radiation oncology treatments [Details]
G. Linan
  • ESANN 2001 - CMOS design of focal plane programmable array processors [Details]
Peggy Lindner
  • ESANN 2021 - Machine Learning for Measuring and Analyzing Online Social Communications [Details]
  • ESANN 2024 - A Two-Stage Approach for Implicit Bias Detection in Generative Language Models [Details]
Gustavo Linhares Vieira
  • ESANN 2018 - An extension of nonstationary fuzzy sets to heteroskedastic fuzzy time series [Details]