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Contents

  • Cooper
  • Overview of Constrained Optimization
  • FAQ
  • Tutorials
    • Linear classification with rate constraints.
    • Finding a spectrum-constrained linear transformation between two vectors.
    • Finding a maximum entropy (discrete) distribution using the Lagrangian Approach.
    • Using the Augmented Lagrangian function.
    • Finding the min-norm solution to a linear system of equations.
    • Learning a Directed Acyclic Graph (DAG) on data.
    • Training a logistic regression classifier on MNIST under a norm constraint.
  • Contributing to Cooper

Package Reference

  • Constrained Minimization Problems
  • Formulations
  • Optim
  • Torch Optimizers
  • Multipliers
  • Penalty Coefficients

Bibliography

  • Bibliography
Cooper
  • Tutorials
  • View page source

Tutorials

List of Tutorials

  • Linear classification with rate constraints.
  • Finding a spectrum-constrained linear transformation between two vectors.
  • Finding a maximum entropy (discrete) distribution using the Lagrangian Approach.
  • Using the Augmented Lagrangian function.
  • Finding the min-norm solution to a linear system of equations.
  • Learning a Directed Acyclic Graph (DAG) on data.
  • Training a logistic regression classifier on MNIST under a norm constraint.
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