- QuadraticProblem.update_linearization(transport, epsilon=None, old_transport_mass=1.0)#
Update linearization of GW problem by updating cost matrix.
If the problem is balanced (
tau_a = 1.0 and tau_b = 1.0), the equation follows eq. 6, p. 1 of [Peyré et al., 2016].
If the problem is unbalanced (
tau_a < 1.0 or tau_b < 1.0), two cases are possible, as explained in
init_linearization()above. Finally, it is also possible to consider a Fused Gromov Wasserstein problem. Details about the resulting cost matrix are also given in
Transport) – Solution of the linearization of the quadratic problem. epsilon: An epsilon scheduler or a float passed on to the linearization. old_transport_mass: Sum of the elements of the transport matrix at the previous iteration.
old_transport_mass (float) –
- Return type
Updated linear OT problem, a new local linearization of GW problem.