First, they demonstrate that SigmoidAttn is a universal function approximator for sequence-to-sequence tasks. Second, they provide an analysis of SigmoidAttn’s regularity and establish its worst-case ...

Maximizing the performance of a system without reference over an infinite horizon is a challenging problem for iterative control tasks. This article introduces a value approximator-based learning ...

Tries to approximate a given image with bezier curves - trenta3/bezier-approximator ...

Assessing the presence and availability of a remote colleague is key in coordination in global software development but is not easily done using existing computer-mediated channels. Previous research ...

To avoid the matrix inversion, we only use such sensitivity-based relation as an efficient approximator to predict the admittance response in the parametric space when carrying out the damage ...

The neural approximator makes the process more efficient. Instead of adding each column one by one, the neural approximator circuit can perform multiple calculations — down columns, across columns, or ...

The neural approximator makes the process more efficient. Instead of adding each column one by one, the neural approximator circuit can perform multiple calculations -- down columns, across ...

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[optional] Basics of Information Theory, a short little tutorial explaining why low-probability events transmit a large number of bits of information. Matlab demos: CMAC models: 1-dimensional function ...