Extreme Learning Machine Based Model Improved with Adaptive Activation Functions

Fonseca, Tales Lima; Goliatt, Leonardo

doi:10.1007/978-3-030-68133-3_12

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Self-learnable Activation Function (Slaf)1

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“…A similar approach was used independently in [572], where authors used the equivalent of SLAF with k = 6. A quadratic variant (i.e., SLAF with k = 2) was used in [573].…”

Section: Self-learnable Activation Function (Slaf)mentioning

confidence: 99%

On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

Kunc

Kléma²

2019

Preprint

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Motivation: Gene expression profiling was made cheaper by the NIH LINCS program that profiles only ∼1, 000 selected landmark genes and uses them to reconstruct the whole profile. The D-GEX method employs neural networks to infer the whole profile. However, the original D-GEX can be further significantly improved. Results: We have analyzed the D-GEX method and determined that the inference can be improved using a logistic sigmoid activation function instead of the hyperbolic tangent. Moreover, we propose a novel transformative adaptive activation function that improves the gene expression inference even further and which generalizes several existing adaptive activation functions. Our improved neural network achieves average mean absolute error of 0.1340 which is a significant improvement over our reimplementation of the original D-GEX which achieves average mean absolute error 0.1637

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“…A similar approach was used independently in [572], where authors used the equivalent of SLAF with k = 6. A quadratic variant (i.e., SLAF with k = 2) was used in [573].…”

Section: Self-learnable Activation Function (Slaf)mentioning

confidence: 99%

On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

Kunc

Kléma²

2019

Preprint

View full text Add to dashboard Cite

show abstract

Extreme Learning Machine Based Model Improved with Adaptive Activation Functions

Cited by 1 publication

References 24 publications

On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

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