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Distance weighted K-Means algorithm for center selection in training radial basis function networks
The accuracies rates of the neural networks mainly depend on the selection of the correct
data centers. The K-means algorithm is a widely used clustering algorithm in various …
data centers. The K-means algorithm is a widely used clustering algorithm in various …
Stochastic trust region inexact Newton method for large-scale machine learning
Nowadays stochastic approximation methods are one of the major research direction to deal
with the large-scale machine learning problems. From stochastic first order methods, now …
with the large-scale machine learning problems. From stochastic first order methods, now …
Saags: Biased stochastic variance reduction methods for large-scale learning
Stochastic approximation is one of the effective approach to deal with the large-scale
machine learning problems and the recent research has focused on reduction of variance …
machine learning problems and the recent research has focused on reduction of variance …
Mean Decision Rules Method with Smart Sampling for Fast Large-Scale Binary SVM Classification
A Makarova, M Kurbakov… - 2020 25th International …, 2021 - ieeexplore.ieee.org
This paper relies on the Mean Decision Rule (MDR) method for solving large-scale binary
SVM problems. It consists in taking small random samples of the full dataset and separate …
SVM problems. It consists in taking small random samples of the full dataset and separate …
[ספר][B] Stochastic optimization for large-scale machine learning
VK Chauhan - 2021 - taylorfrancis.com
Advancements in the technology and availability of data sources have led to theBig
Data'era. Working with large data offers the potential to uncover more fine-grained patterns …
Data'era. Working with large data offers the potential to uncover more fine-grained patterns …
[HTML][HTML] LIBS2ML: A library for scalable second order machine learning algorithms
Most of the machine learning libraries are either in MATLAB/Python/R which are very slow
and not suitable for large-scale learning, or are in C/C++ which does not have easy ways to …
and not suitable for large-scale learning, or are in C/C++ which does not have easy ways to …
Fast Approximate Decision of Large-Scale SVM-regression Problems
In this paper we propose a new method that allows us to quickly find an approximate, but not
significantly different from the exact solution of large-scale SVM regression problems: it has …
significantly different from the exact solution of large-scale SVM regression problems: it has …
[CITATION][C] SAAGs: Biased Stochastic Variance Reduction Methods.
VK Chauhan, A Sharma, K Dahiya - arxiv preprint arxiv:1807.08934, 2018