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cs.CL2024★ 1 cited
What Happens When Small Is Made Smaller? Exploring the Impact of Compression on Small Data Pretrained Language Models
Busayo Awobade, Mardiyyah Oduwole, Steven Kolawole
Compression techniques have been crucial in advancing machine learning by enabling efficient training and deployment of large-scale language models. However, these techniques have…
math.OC2024★ 1 cited
A robust regularized extreme learning machine for regression problems based on self-adaptive accelerated extra-gradient algorithm
Muideen Adegoke, Lateef O. Jolaoso, Mardiyyah Oduwole
The Extreme Learning Machine (ELM) technique is a machine learning approach for constructing feed-forward neural networks with a single hidden layer and their models. The ELM model…