Integer-Only Operations on Extreme Learning Machine Test Time Classification

ArXi:2604.04363v1 Announce Type: cross 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.