Description: Regularization, in mathematics and statistics and particularly in the fields of machine learning and inverse problems, refers to a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting. This information is usually of the form of a penalty for complexity, such as restrictions for smoothness or bounds on the vector space norm.
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File list (Check if you may need any files):
regu\app_hh.m
....\art.m
....\baart.m
....\bidiag.m
....\blur.m
....\cgls.m
....\cgsvd.m
....\Changes.txt
....\Contents.m
....\corner.m
....\csvd.m
....\deriv2.m
....\discrep.m
....\dsvd.m
....\fil_fac.m
....\foxgood.m
....\gcv.m
....\gcvfun.m
....\gen_form.m
....\gen_hh.m
....\get_l.m
....\gravity.m
....\heat.m
....\i_laplace.m
....\lagrange.m
....\lanc_b.m
....\lcfun.m
....\lsolve.m
....\lsqi.m
....\lsqr_b.m
....\ltsolve.m
....\l_corner.m
....\l_curve.m
....\maxent.m
....\mr2.m
....\mtsvd.m
....\ncp.m
....\ncpfun.m
....\nu.m
....\parallax.m
....\pcgls.m
....\phillips.m
....\picard.m
....\pinit.m
....\plot_lc.m
....\plsqr_b.m
....\pmr2.m
....\pnu.m
....\prrgmres.m
....\quasifun.m
....\quasiopt.m
....\regudemo.m
....\regutm.m
....\rrgmres.m
....\shaw.m
....\spikes.m
....\spleval.m
....\splsqr.m
....\splsqrL.m
....\std_form.m
....\tgsvd.m
....\tikhonov.m
....\tomo.m
....\tsvd.m
....\ttls.m
....\ursell.m
....\wing.m
RTv4manual.pdf
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