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Why? The concept of AutoML does include the design of novel algorithms.

• p1esk 8y ago
  What do you mean? I thought AutoML was a tool to do neural architecture search, and hyperparameter tuning.
  • human_scientist 8y ago
    The field of automatic machine learning (abbreviated as AutoML) concerns all endeavours to automate the process of machine learning. To provide a sense of what could constitute AutoML, let me post a list from the "Call for Papers" of the International Workshop on Automatic Machine Learning (ICML 2018) [1]: * Model selection, hyper-parameter optimization, and model search * Neural architecture search * Meta learning and transfer learning * Automatic feature extraction / construction * Demonstrations (demos) of working AutoML systems * Automatic generation of workflows / workflow reuse * Automatic problem "ingestion" (from raw data and miscellaneous formats) * Automatic feature transformation to match algorithm requirements * Automatic detection and handling of skewed data and/or missing values * Automatic acquisition of new data (active learning, experimental design) * Automatic report writing (providing insight on automatic data analysis) * Automatic selection of evaluation metrics / validation procedures * Automatic selection of algorithms under time/space/power constraints * Automatic prediction post-processing and calibration * Automatic leakage detection * Automatic inference and differentiation * User interfaces and human-in-the-loop approaches for AutoML [1] https://sites.google.com/site/automl2018icml/ https://sites.google.com/site/automl2018icml/
    • p1esk 8y ago
      I don't see "Automatic design of novel algorithms" in this list. Can AutoML produce something as novel as a GAN, CapsNet, WaveNet, Transformer, Neural ODE, etc? Is that even considered to be one of its goals? In my opinion, there's a clear separation between a group of people trying to improve AutoML so that it's more useful in doing all those tasks on the list, and a group of people trying to invent next gen ML algorithms or DL architectures.
    • human_scientist 8y ago
      > I don't see "Automatic design of novel algorithms" in this list. Can AutoML produce something as novel as a GAN, CapsNet, WaveNet, Transformer, Neural ODE, etc? Is that even considered to be one of its goals. In my opinion, there's a clear separation between a group of people trying to improve AutoML so that it's more useful in doing all those tasks on the list, and a group of people trying to invent next gen ML algorithms or DL architectures. I agree with you from the view of the current state of the art methods and the current state of the AutoML / fundamental ML research communities. Current methods are very limited, but I can not think of a reason why a sufficiently general searchspace of architectures/pipelines could not produce something like a GAN or a WaveNet. I do not think that designing algorithms as novel as the ones you listed is currently a goal of AutoML, as that is not something we have an attack for. However, I do think that with increasing capabilities, the field of AutoML will seek to automate every step of the machine learning pipeline - including the design of algorithms. E.g., once/if there are attacks to apply NAS for yielding truly novel architectures, I think NAS researchers will be happy to do just that -- wouldn't you call that AutoML then?
      • p1esk 8y ago
        sufficiently general searchspace But that would require enormous computing resources!