D15-1183 vocabulary are infrequent , and Tikhonov regularization is necessary for them . It is
D15-1183 are enough frequent , and thus Tikhonov regularization is unnecessary . In this case
D15-1183 comparing to PSD-Unreg-180K , we see Tikhonov regularization brings 1-4 % performance boost
D15-1183 approxi - mation , subject to Tikhonov regularization . Then we adopt a Block Coordinate
D15-1183 all µi = 0 , i.e. disabling Tikhonov regularization . PSD-Reg-180K was trained with
D15-1183 approximant X of G * , subject to Tikhonov regularization . This problem does not admit
W04-0851 binary classification problems via Tikhonov regularization in a Reproducing Kernel Hilbert
W04-0851 learning based on kernels and Tikhonov regularization . In the next section we explain
W03-0613 that they are both instances of Tikhonov regularization ( Evgeniou et al. , 2000 ) ,
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