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
Stéphane Rivaud
  • ESANN 2025 - Growth strategies for arbitrary DAG neural architectures [Details]
C. Rivero
  • ESANN 2003 - Characterization of the absolutely expedient learning algorithms for stochastic automata in a non-discrete space of actions [Details]
Bertrand Rivet
  • ESANN 2021 - Fusion of estimations from two modalities using the Viterbi's algorithm: application to fetal heart rate monitoring [Details]
Bertrand Rivet
  • ESANN 2009 - Sensors selection for P300 speller brain computer interface [Details]
  • ESANN 2012 - Application of Dynamic Time Warping on Kalman Filtering Framework for Abnormal ECG Filtering [Details]
I. Rizzi
  • ESANN 2001 - Applications of neuro-fuzzy classification, evaluation and forecasting techniques in agriculture [Details]
Antonio Rizzo
  • ESANN 2025 - Introducing Intrinsic Motivation in Elastic Decision Transformers [Details]
Sylvain Robbiano
  • ESANN 2015 - An Ensemble Learning Technique for Multipartite Ranking [Details]
A. Röbel
  • ESANN 1994 - Dynamic pattern selection for faster learning and controlled generalization of neural networks [Details]
Isaac Roberts
  • ESANN 2024 - Visualizing and Improving 3D Mesh Segmentation with DeepView [Details]
  • ESANN 2025 - Conceptualizing Concept Drift [Details]
Stephen J Roberts
  • ESANN 2020 - Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks [Details]
Audrey Robinel
  • ESANN 2012 - Real time drunkenness analysis in a realistic car simulation [Details]
  • ESANN 2013 - Multi-user Blood Alcohol Content estimation in a realistic simulator using Artificial Neural Networks and Support Vector Machines [Details]
Mark Robinson
  • ESANN 2006 - Using sampling methods to improve binding site predictions [Details]
J. Robinson
  • ESANN 1994 - Stability and bifurcation in an autoassociative memory model [Details]
Langone Rocco
  • ESANN 2014 - Agglomerative hierarchical kernel spectral clustering for large scale networks [Details]
Christoph Roch
  • ESANN 2020 - Approximating Archetypal Analysis Using Quantum Annealing [Details]
Gil Rocha
  • ESANN 2021 - Towards Robust Auxiliary Tasks for Language Adaptation [Details]
Honovan Rocha
  • ESANN 2015 - Training Multi-Layer Perceptron with Multi-Objective Optimization and Spherical Weights Representation [Details]
M. Rocha
  • ESANN 2001 - Lamarckian training of feedforward neural networks [Details]
  • ESANN 2003 - Adaptive Learning in Changing Environments [Details]
Ajalmar Rocha Neto
  • ESANN 2016 - Sparse Least Squares Support Vector Machines via Multiresponse Sparse Regression [Details]
  • ESANN 2018 - Opposite neighborhood: a new method to select reference points of minimal learning machines [Details]
  • ESANN 2019 - Sparse minimal learning machine using a diversity measure minimization [Details]
O. Rochel
  • ESANN 2003 - An event-driven framework for the simulation of networks of spiking neurons [Details]
Ali Rodan
  • ESANN 2011 - Negatively Correlated Echo State Networks [Details]
  • ESANN 2012 - Short Term Memory Quantifications in Input-Driven Linear Dynamical Systems [Details]
  • ESANN 2018 - Forecasting Business Failure in Highly Imbalanced Distribution based on Delay Line Reservoir [Details]
Manuel Röder
  • ESANN 2024 - Sparse Uncertainty-Informed Sampling from Federated Streaming Data [Details]
  • ESANN 2025 - Resource-Aware Cooperation in Federated Learning [Details]
Manuel Röder
  • No papers found
Manuel Röder
  • ESANN 2022 - Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification [Details]
Erik Rodner
  • ESANN 2016 - Watch, Ask, Learn, and Improve: a lifelong learning cycle for visual recognition [Details]
Antonio Wendell Rodrigues
  • ESANN 2016 - Sparse Least Squares Support Vector Machines via Multiresponse Sparse Regression [Details]
Thiago Rodrigues
  • ESANN 2008 - A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy [Details]
Leonardo Rodrigues
  • ESANN 2016 - K-means for Datasets with Missing Attributes: Building Soft Constraints with Observed and Imputed Values [Details]
  • ESANN 2016 - Using Robust Extreme Learning Machines to Predict Cotton Yarn Strength and Hairiness [Details]
Sergio Rodrigues de Morais
  • ESANN 2008 - Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification [Details]
Sinvaldo Rodrigues Moreno
  • No papers found