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It is well known that MRFs are the most general models used as priors during regularization when solving ill-posed problems [34].
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In practice, we had to address how to determine critical empirical parameters during the regularization process: they were (1) the regularization parameter, λ (2) the value of gamma, γ, for the weight matrix M, (3) the number of iterations in PCG, NI PCG, and (4) Newton's steps, NS Newton.
Tailorings of other device parameters that could potentially affect the %VP, such as rate-adaptive AV, automatic post-ventricular atrial refractory period, conducted AF response (i.e. ventricular rate regularization during AF), lead impedance trend which collects lead impedance data during pacing, and so forth, were also committed to each participant clinician.
Flash3D [4] is basically an ordered subset expectation maximization (OSEM) algorithm without any particular noise regularization during the iterations.
The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process.
Second, we apply a refinement of the Multi-Task Sparse Learning (MTSL) framework to exploit the relationships among multiple shared tasks generated by changing the regularization parameter during the recognition stage.
The spheres reconstructed using NM 530c are more uniform due to the noise regularization applied during the NM 530c reconstruction and the Butterworth post-filtering, but are similar in shape to those obtained using MCR.
The ridge regression regularization used during parameter fitting automatically chooses the best time offset(s) by suppressing the weight coefficients of less useful time offsets.
The regularization technique applied during the inversion process smoothes the magnetic field model in time.
The parameter controlling the regularization is changed during the evolution of the dynamical system to render inefficient local solutions (which formerly were stable) unstable, thus conducting the system to escape from sub-optimal points, and so to improve the final results.
The test fold was used to evaluate this best model these results are reported in Section 7. The range of values we tried during the tuning of the regularization parameter were 150 10−4.
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