skglm.solvers.FISTA¶

class skglm.solvers.FISTA(max_iter=100, tol=0.0001, opt_strategy='subdiff', verbose=0)[source]¶

ISTA solver with Nesterov acceleration (FISTA).

References

[1]

Beck, A. and Teboulle M. “A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse problems”, 2009, SIAM J. Imaging Sci. https://epubs.siam.org/doi/10.1137/080716542

Attributes:

max_iterint, default 100: Maximum number of iterations.
tolfloat, default 1e-4: Tolerance for convergence.
verbosebool, default False: Amount of verbosity. 0/False is silent.

__init__(max_iter=100, tol=0.0001, opt_strategy='subdiff', verbose=0)[source]¶

Methods

`__init__`([max_iter, tol, opt_strategy, verbose])
`custom_checks`(X, y, datafit, penalty)	Ensure the solver is suited for the datafit + penalty problem.
`solve`(X, y, datafit, penalty[, w_init, ...])	Solve the optimization problem after validating its compatibility.