White Box Network: Obtaining a right composition ordering of functionsDownload PDF

25 Sep 2019 (modified: 24 Dec 2019)ICLR 2020 Conference Blind SubmissionReaders: Everyone
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  • Keywords: white box, black box, function composition, neural network, ordering functions, reverse engineering, programmable logic controller, plc, white box network, WBN
  • TL;DR: We presented a new model called the WBN, which obtains the exact order and correct inputs of function blocks to compose them for constructing target functions.
  • Abstract: Neural networks have significantly benefitted real-world tasks. The universality of a neural network enables the approximation of any type of continuous functions. However, a neural network is regarded as a non-interpretable black box model, and this is fatal to reverse engineering as the main goal of reverse engineering is to reveal the structure or design of a target function instead of approximating it. Therefore, we propose a new type of a function constructing network, called the white box network. This network arranges function blocks to construct a target function to reveal its design. The network uses discretized layers, thus rendering the model interpretable without disordering the function blocks. Additionally, we introduce an end-to-end PathNet structure through this discretization by considering the function blocks as neural networks
  • Code: https://github.com/ekRmxskTek/WBN/
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