Results 1 to 10 of about 285,904 (328)

SMART: unique splitting-while-merging framework for gene clustering. [PDF]

PLoS ONE, 2014
Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori.
Rui Fa, David J Roberts, Asoke K Nandi
doaj   +5 more sources

A Decision Tree Classification Algorithm Based on Two-Term RS-Entropy [PDF]

Entropy
Classification is an important task in the field of machine learning. Decision tree algorithms are a popular choice for handling classification tasks due to their high accuracy, simple algorithmic process, and good interpretability.
Ruoyue Mao, Xiaoyang Shi, Zhiyan Shi
doaj   +2 more sources

Modified Tseng's splitting algorithms for the sum of two monotone operators in Banach spaces

AIMS Mathematics, 2021
In this work, we introduce two modified Tseng's splitting algorithms with a new non-monotone adaptive step size for solving monotone inclusion problem in the framework of Banach spaces.
Jun Yang, Prasit Cholamjiak, Pongsakorn Sunthrayuth   +2 more
doaj   +2 more sources

A Generalized Matrix Splitting Algorithm [PDF]

, 2018
Composite function minimization captures a wide spectrum of applications in both computer vision and machine learning. It includes bound constrained optimization, $\ell_1$ norm regularized optimization, and $\ell_0$ norm regularized optimization as special cases.
Ganzhao Yuan, Wei‐Shi Zheng, Li Shen, Bernard Ghanem   +3 more
openalex   +3 more sources

Higher-order splitting algorithms for solving the nonlinear Schr\"odinger equation and their instabilities [PDF]

, 2007
Since the kinetic and the potential energy term of the real time nonlinear Schr\"odinger equation can each be solved exactly, the entire equation can be solved to any order via splitting algorithms.
B. Leimkuhler, C. J. Pethick, E. Hairer, G. B. Whitham, N. N. Bogoliubov, R. I. McLachlan, R. I. McLachlan, Siu A. Chin   +7 more
core   +5 more sources

The unresolved struggle of 16S rRNA amplicon sequencing: a benchmarking analysis of clustering and denoising methods [PDF]

Environmental Microbiome
Background Although 16S rRNA gene amplicon sequencing has become an indispensable method for microbiome studies, this analysis is not error-free, and remains prone to several biases and errors.
Mohamed Fares, Engy K. Tharwat, Ilse Cleenwerck, Pieter Monsieurs, Rob Van Houdt, Peter Vandamme, Mohamed El-Hadidi, Mohamed Mysara   +7 more
doaj   +2 more sources

Efficient splitting off algorithms for graphs [PDF]

Proceedings of the twenty-sixth annual ACM symposium on Theory of computing - STOC '94, 1994
Harold N. Gabow
openalex   +2 more sources

Split-Douglas--Rachford Algorithm for Composite Monotone Inclusions and Split-ADMM [PDF]

SIAM Journal on Optimization, 2021
26 ...
Luis M. Bricen͂o-Arias, Fernando Roldán   +1 more
openaire   +2 more sources

Shear-Wave Splitting Analysis Using Optimization Algorithms

Lithosphere, 2022
Shear-wave splitting (SWS) analysis is used to predict fractures in subsurface media. Specifically, two parameters relevant to SWS analysis (the azimuth of the fast shear wave and the time delay between the fast and slow shear waves) are used to quantify
Zhengtao He, Yuyong Yang, Huailai Zhou
doaj   +1 more source

Factors Affecting Landslide Susceptibility Mapping: Assessing the Influence of Different Machine Learning Approaches, Sampling Strategies and Data Splitting

Land, 2021
Data driven methods are widely used for the development of Landslide Susceptibility Mapping (LSM). The results of these methods are sensitive to different factors, such as the quality of input data, choice of algorithm, sampling strategies, and data ...
Minu Treesa Abraham, Neelima Satyam, Revuri Lokesh, Biswajeet Pradhan, Abdullah Alamri   +4 more
doaj   +1 more source