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Create Multi-Objectives Optimization Benchmarks for Deep Neural Networks. #6

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Create Multi-Objectives Optimization Benchmarks for Deep Neural Networks.#6
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thchang

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@Deathn0t
Deathn0t
opened on Mar 10, 2023

Similarly to ECP-Candle and PINNBench benchmarks some new benchmarks compatible with Multi-Objective Optimization (MOO) should be defined. They could be "extensions" of the already existing benchmark but compatible with MOO.

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  1. Deathn0t
    assigned
    thchang
    on Mar 17, 2023

  2. Deathn0t commented on Mar 17, 2023

    @Deathn0t
    Deathn0t
    on Mar 17, 2023
    MemberAuthor

    I discovered 2 benchmarks related to MOO for Deep Neural Networks (AutoML):

    • YAHPO
    • JAHS-Bench-201
      I created the corresponding folders in the lib/ directory with a link to the Github repository of these benchmarks in the README.md.

  3. thchang commented on Mar 17, 2023

    @thchang
    thchang
    on Mar 17, 2023
    Contributor

    Thanks, I'll check this out when I'm done with the analytical test funcitons for #5

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