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Machine Learning and ELM

TopicLeading institutions, researchers & key papers

Machine Learning and ELM is a topic indexed in ScholarIQ from OpenAlex.

What is known about Machine Learning and ELM?

ScholarIQrecord summary

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.

How many works does Machine Learning and ELM have?

ScholarIQindexed works

Machine Learning and ELM has 17,101 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

How many citations does Machine Learning and ELM have?

ScholarIQcitation count

Machine Learning and ELM has 268,129 citations in the OpenAlex counts ScholarIQ stores.

What is the OpenAlex record for Machine Learning and ELM?

ScholarIQopenalex

The OpenAlex for Machine Learning and ELM is on the source record.

Who are the most-cited researchers behind Machine Learning and ELM?

ScholarIQtop researchers by citations
1
Yoshua Bengio · Neural Networks and Applications
1,290 works476,190 citations
2
Andrew Zisserman · Advanced Image and Video Retrieval Techniques
949 works259,063 citations
3
Yann LeCun · Domain Adaptation and Few-Shot Learning
484 works252,968 citations
4
Vladimir Vapnik · Neural Networks and Applications
150 works225,637 citations
5
Trevor Darrell · Multimodal Machine Learning Applications
867 works205,979 citations

Where is Machine Learning and ELM research published, and who funds it?

ScholarIQvenues & funding sources

TOP JOURNALS

No journal data available yet.

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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