Integer-Only Operations on Extreme Learning Machine Test Time Classification

📰 ArXiv cs.AI

Extreme Learning Machine test time classification can be performed using solely integer operations without compromising accuracy

advanced Published 7 Apr 2026

Action Steps

Derive characteristics from Extreme Learning Machine models
Explore integer-only operations for test time classification
Evaluate the impact on classification accuracy and computational cost

Who Needs to Know This

ML researchers and engineers working on efficient neural network implementations can benefit from this research to optimize their models for better performance and reduced computational cost

Key Insight

💡 Integer-only operations can be used for ELM test time classification without compromising accuracy

Key Takeaways

Extreme Learning Machine test time classification can be performed using solely integer operations without compromising accuracy

Full Article

Title: Integer-Only Operations on Extreme Learning Machine Test Time Classification

Abstract:
arXiv:2604.04363v1 Announce Type: cross Abstract: We present a theoretical analysis and empirical evaluations of a novel set of techniques for computational cost reduction of test time operations of network classifiers based on extreme learning machine (ELM). By exploring some characteristics we derived from these models, we show that the classification at test time can be performed using solely integer operations without compromising the classification accuracy. Our contributions are as follows

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