[图书][B] Real life applications of soft computing

A Shukla, R Tiwari, R Kala - 2010 - books.google.com
Rapid advancements in the application of soft computing tools and techniques have proven
valuable in the development of highly scalable systems. Although many resources on the …

Spiking neuron networks a survey

H Paugam-Moisy - 2006 - infoscience.epfl.ch
Abstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd generation of
neural networks. They derive their strength and interest from an accurate modelling of …

[PDF][PDF] Large scale machine learning

R Collobert - 2004 - infoscience.epfl.ch
This thesis aims to address machine learning in general, with a particular focus on large
models and large databases. After introducing the learning problem in a formal way, we first …

Fuzzy neuro systems for machine learning for large data sets

R Kala, A Shulkla, R Tiwari - 2009 IEEE International Advance …, 2009 - ieeexplore.ieee.org
Artificial Neural Networks have found a variety of applications that cover almost every
domain. The increasing use of Artificial Neural Networks and machine learning has led to a …

Parallel approach for ensemble learning with locally coupled neural networks

C Valle, F Saravia, H Allende, R Monge… - Neural processing …, 2010 - Springer
Ensemble learning has gained considerable attention in different tasks including regression,
classification and clustering. Adaboost and Bagging are two popular approaches used to …

Parallel development and deployment for machine learning models

B Qin, F Azam, D Malov - US Patent 10,482,389, 2019 - Google Patents
Example systems and methods of developing a learning model are presented. In one
example, a sample data set to train a first learning algorithm is accessed. A number of states …

Damned: A distributed and multithreaded neural event-driven simulation framework

A Mouraud, D Puzenat, H Paugam-Moisy - arXiv preprint cs/0512018, 2005 - arxiv.org
In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed
both in time and in the network architecture. Since a current feature of SNNs is a low …

A parallel evolving algorithm for flexible neural tree

L Peng, B Yang, L Zhang, Y Chen - Parallel Computing, 2011 - Elsevier
In the past few decades, much success has been achieved in the use of artificial neural
networks for classification, recognition, approximation and control. Flexible neural tree (FNT) …

Computational grid vs. parallel computer for coarse-grain parallelization of neural networks training

V Turchenko - OTM Confederated International Conferences" On the …, 2005 - Springer
Abstract Development of a coarse-grain parallel algorithm of artificial neural networks
training with dynamic mapping onto processors of parallel computer system is considered in …

Distributed processing for modelling real-time multimodal perception in a virtual robot

S Chevallier, H Paugam-Moisy, F Lemaître - PDCN'2005, 2005 - hal.science
Built from a need for modelling cognitive processes, a modular neural network is designed
as the" brain" of a virtual robot moving in a prey-predator environment. The robot decides its …