fahrbach / subquadratic-kronecker-regression

Subquadratic Kronecker regression with applications to tensor decomposition (NeurIPS 2022)

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subquadratic-kronecker-regression

Files

  • kronecker_regression_main.py -- Implementation of FastKroneckerRegression and DJSSW19.
  • run_all_kronecker_regression.py -- Wrapper to generate Figure 1 and Table 1.
  • tucker_als.py -- Library with KronMatMul and TuckerALS implementations.
  • tucker_decomposition_experiments.py -- Main file for running Tucker decomposition with command line arguments.
  • run_all_tensor_decomposition.py -- Wrapper to run all Tucker decomposition experiments.
  • tensor_data_handler.py -- Handler class to read different tensor data into np.ndarray format.
  • data/ -- Contains instructions on how to generate all of our datasets.
  • output/ -- Contains the output logs for all of our Kronecker regression and tensor decomposition experiments.
  • plots/ -- Contains code to generate Figure 1.

Instructions

  • $ python3 run_all_kronecker_regression.py
  • $ python3 run_all_tensor_decomposition.py

About

Subquadratic Kronecker regression with applications to tensor decomposition (NeurIPS 2022)

License:MIT License


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