BenchOpt bnechmark for Convolutional Sparse Coding =====================

BenchOpt is a package to simplify and make more transparent and reproducible the comparisons of optimization algorithms. This benchmark is dedicated to solver of convolutional sparse coding:

$$\min_{w > 0} \frac{1}{2} \|y - X * w\|^2_2 + \lambda \|w\|_1$$

where n (or n_samples) stands for the number of samples, p (or n_features) stands for the number of features and

X = [x₁^⊤, …, x_n^⊤]^⊤ ∈ ℝ^n × p

Install

This benchmark can be run using the following commands:

$ pip install -U benchopt
$ git clone https://github.com/benchopt/benchmark_csc
$ benchopt run ./benchmark_csc

Apart from the problem, options can be passed to benchopt run, to restrict the benchmarks to some solvers or datasets, e.g.:

$ benchopt run benchmark_csc -s alphacsc -d simulated --max-runs 10 --n-repetitions 10

Use benchopt run -h for more details about these options, or visit https://benchopt.github.io/api.html.