Convex optimization for machine learning

  • Is convex optimization used in machine learning?

    Convex optimization has become an essential tool in machine learning because many real-world problems can be modeled as convex optimization problems.
    For example, in classification problems, the goal is to find the best hyperplane that separates the data points into different classes.Mar 29, 2023.

  • Which optimization algorithm is best for machine learning?

    Top Optimisation Methods In Machine Learning

    Gradient Descent.
    The gradient descent method is the most popular optimisation method. Stochastic Gradient Descent. Adaptive Learning Rate Method. Conjugate Gradient Method. Derivative-Free Optimisation. Zeroth Order Optimisation. For Meta Learning..

  • Convex problems, if possible, will be one of the best alternative.
    However, convex optimizations in Neural Networks are still in development with the nature that Neural Networks is non-convex.
    CVXPY still needs to define the objective function to solve, and current cost functions in use isn't suitable for it.

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