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Machine Learning and ELM
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the theory, applications, and advancements in Extreme Learning Machines (ELM), a machine learning framework based on feedforward neural networks with random hidden nodes. The papers cover topics such as incremental learning, classification, regression, ensemble methods, kernel-based models, and their applications in various domains.
79
Works
IDs:OpenAlex
How has Machine Learning and ELM's publication output changed over time?
ScholarIQpublication output · 2011–2024
Output grew0% over the shown period — from 1 works in 2011 to 1 in 2024.
1
1
4
1
1
2
1
1
2
1
2011201220152017201820192020202120222024
What are the most-cited papers on Machine Learning and ELM?
ScholarIQmost cited works
A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification
Abdu Gumaei, Mohammad Mehedi Hassan, Md. Rafiul Hassan, Abdulhameed Alelaiwi, Giancarlo Fortino
IEEE Access. 2019474 CitationsOPEN ACCESS
Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy
Zhennao Cai, Jianhua Gu, Jie Luo, Qian Zhang, Huiling Chen, Zhifang Pan, Yuping Li, Chengye Li
Expert Systems with Applications. 2019248 Citations
An improved cuckoo search based extreme learning machine for medical data classification
Puspanjali Mohapatra, Sujata Chakravarty, Priyabrata Dash
Swarm and Evolutionary Computation. 2015190 Citations
Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine
Vivek Lahoura, Harpreet Singh, Ashutosh Aggarwal, Bhisham Sharma, Mazin Abed Mohammed, Robertas Damaševičius, Seifedine Kadry, Korhan Cengiz
Diagnostics. 2021183 CitationsOPEN ACCESS
Online sequential extreme learning machine with forgetting mechanism
Jianwei Zhao, Zhihui Wang, Dong Sun Park
S45693802. 2012180 Citations
Where is Machine Learning and ELM research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Machine Learning and ELM is open access?
ScholarIQopen access share
40%OPEN ACCESS
Gold
33%
Green
0%
Hybrid
7%
Bronze
0%
Closed
60%
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