In order to avoid overfitting and enhance the generalization ability, we regularize the L2-norm of the parameters as in ridge regression with a penalization parameter λ.
Recently, Moudafi and Maingé [2] studied the VI (1.2) by regularizing the mapping and defined as the unique fixed point of the equation (1.3).
Very recently, Lu et al. [3] studied the VI (1.2) by regularizing the mapping and defined as the unique fixed point of the equation (1.4).
Further, the TSSG tracker is novel in exploiting the sparsity present in the grid-based state vector, which allows one to leverage efficient solvers of (weighted) least-squares (LS) minimization problems regularized by the ℓ1-norm of the desired state estimate.
(2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph.
By regularizing the complex filter function, phase degradation by noise amplification is suppressed as anticipated from intensity deconvolution [ 14].
The solution are obtained by regularizing the system of equations by means of the TSVD method.
Furthermore, the similarity between the tasks is facilitated by regularizing the task specific weights.
The solution is obtained by regularizing the system of equations by the Tikhonov method.
They proved two strong convergence results by regularizing the nonexpansive mapping T using contractions.
