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Inference and Divergence in Machine Learning
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Inference and Divergence in Machine Learning

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Questions and Answers

What is typically required when applying statistical techniques in practice?

  • Accurate knowledge of the statistical model
  • Imposing assumptions on the underlying statistics (correct)
  • Data-driven schemes only
  • Infeasible analytical expressions

    • Why does inaccurate model knowledge lead to degraded performance in model-based techniques?

  • Availability of accurate statistical modeling
  • Due to data-driven schemes taking over
  • Result of estimation errors (correct)
  • Simplicity in expressing environment dynamics

    • In which scenarios does the limited applicability of model-based schemes arise?

  • When estimation errors occur
  • When analysis is too complex
  • When P is unknown or costly to estimate accurately (correct)
  • When P is known accurately

    • What do data-driven systems learn their mapping from?

    <p>Data</p> Signup and view all the answers

    Why is it infeasible to come up with an analytical expression for the conditional distribution of a breed of a dog label given an image of a dog?

    <p>Complexity in the environment dynamics</p> Signup and view all the answers

    What does degraded performance in model-based techniques result from?

    <p>Enforcing a model not capturing the environment fully</p> Signup and view all the answers

    How do data-driven systems learn their mapping?

    <p>By learning from data</p> Signup and view all the answers

    What limits the applicability of model-based schemes in certain scenarios?

    <p>Unknown or costly-to-estimate variables like P</p> Signup and view all the answers

    Why are assumptions imposed on underlying statistics when applying statistical techniques?

    <p>Due to inaccuracy in model knowledge availability</p> Signup and view all the answers

    What is one major advantage data-driven systems have over model-based techniques?

    <p>Learning mapping from data when statistical modeling is difficult</p> Signup and view all the answers

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