Randomness in neural networks: an overview

Insights into randomized algorithms for neural networks: Practical issues and common pitfalls

(2017) Ming Li et al.   INFORMATION SCIENCES

Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]

(2016) Ye Ren et al.   IEEE Computational Intelligence Magazine

A semi-supervised random vector functional-link network based on the transductive framework

(2016) Simone Scardapane et al.   INFORMATION SCIENCES

Editorial: Randomized algorithms for training neural networks

(2016) Dianhui Wang   INFORMATION SCIENCES

A comprehensive evaluation of random vector functional link networks

(2016) Le Zhang et al.   INFORMATION SCIENCES

A survey of randomized algorithms for training neural networks

(2016) Le Zhang et al.   INFORMATION SCIENCES

Approximation with random bases: Pro et Contra

(2016) Alexander N. Gorban et al.   INFORMATION SCIENCES

A decentralized training algorithm for Echo State Networks in distributed big data applications

(2016) Simone Scardapane et al.   NEURAL NETWORKS

Universal Approximation with Convex Optimization: Gimmick or Reality? [Discussion Forum]

(2015) Jose C. Principe et al.   IEEE Computational Intelligence Magazine

Distributed learning for Random Vector Functional-Link networks

(2015) Simone Scardapane et al.   INFORMATION SCIENCES

A probabilistic learning algorithm for robust modeling using neural networks with random weights

(2015) Feilong Cao et al.   INFORMATION SCIENCES

Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes

(2015) Nikola Kasabov et al.   INFORMATION SCIENCES

Prediction of telephone calls load using Echo State Network with exogenous variables

(2015) Filippo Maria Bianchi et al.   NEURAL NETWORKS

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

On Learning Navigation Behaviors for Small Mobile Robots With Reservoir Computing Architectures

(2015) Eric Aislan Antonelo et al.   IEEE Transactions on Neural Networks and Learning Systems

Hardware implementation methods in Random Vector Functional-Link Networks

(2014) José M. Martínez-Villena et al.   APPLIED INTELLIGENCE

Bag Constrained Structure Pattern Mining for Multi-Graph Classification

(2014) Jia Wu et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Fast decorrelated neural network ensembles with random weights

(2014) Monther Alhamdoosh et al.   INFORMATION SCIENCES

Sparse algorithms of Random Weight Networks and applications

(2013) Feilong Cao et al.   EXPERT SYSTEMS WITH APPLICATIONS

Acoustic Modeling With Hierarchical Reservoirs

(2013) Fabian Triefenbach et al.   IEEE Transactions on Audio Speech and Language Processing

Reply to the Comments on the “No-Prop” algorithm

(2013) Bernard Widrow   NEURAL NETWORKS

Learning the pseudoinverse solution to network weights

(2013) J. Tapson et al.   NEURAL NETWORKS

Real-Time Parallel Processing of Grammatical Structure in the Fronto-Striatal System: A Recurrent Network Simulation Study Using Reservoir Computing

(2013) Xavier Hinaut et al.   PLoS One

Simple Deterministically Constructed Cycle Reservoirs with Regular Jumps

(2012) Ali Rodan et al.   NEURAL COMPUTATION

Design Strategies for Weight Matrices of Echo State Networks

(2012) Tobias Strauss et al.   NEURAL COMPUTATION

Echo State Property Linked to an Input: Exploring a Fundamental Characteristic of Recurrent Neural Networks

(2012) G. Manjunath et al.   NEURAL COMPUTATION

Re-visiting the echo state property

(2012) Izzet B. Yildiz et al.   NEURAL NETWORKS

The No-Prop algorithm: A new learning algorithm for multilayer neural networks

(2012) Bernard Widrow et al.   NEURAL NETWORKS

Prediction for noisy nonlinear time series by echo state network based on dual estimation

(2012) Chunyang Sheng et al.   NEUROCOMPUTING

Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing

(2012) L. Larger et al.   OPTICS EXPRESS

Recent Advances of Large-Scale Linear Classification

(2012) Guo-Xun Yuan et al.   PROCEEDINGS OF THE IEEE

Optoelectronic Reservoir Computing

(2012) Y. Paquot et al.   Scientific Reports

Kernel Recursive Least-Squares Tracker for Time-Varying Regression

(2012) S. Van Vaerenbergh et al.   IEEE Transactions on Neural Networks and Learning Systems

Chaotic Time Series Prediction Based on a Novel Robust Echo State Network

(2012) Decai Li et al.   IEEE Transactions on Neural Networks and Learning Systems

Efficient Additive Kernels via Explicit Feature Maps

(2011) A. Vedaldi et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Recurrent Kernel Machines: Computing with Infinite Echo State Networks

(2011) Michiel Hermans et al.   NEURAL COMPUTATION

Information processing in echo state networks at the edge of chaos

(2011) Joschka Boedecker et al.   THEORY IN BIOSCIENCES

Information processing using a single dynamical node as complex system

(2011) L. Appeltant et al.   Nature Communications

Nonlinear System Modeling With Random Matrices: Echo State Networks Revisited

(2011) Bai Zhang et al.   IEEE Transactions on Neural Networks and Learning Systems

Minimum Complexity Echo State Network

(2010) A Rodan et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

Hierarchy and dynamics of neural networks

(2010) Marcus Kaiser   Frontiers in Neuroinformatics

Kernel methods in machine learning

(2008) Thomas Hofmann et al.   ANNALS OF STATISTICS

Short-term stock price prediction based on echo state networks

(2008) Xiaowei Lin et al.   EXPERT SYSTEMS WITH APPLICATIONS

Improving reservoirs using intrinsic plasticity

(2008) Benjamin Schrauwen et al.   NEUROCOMPUTING