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@@ -147,8 +147,6 @@ void FastMinKernel::hik_prepare_alpha_multiplications(const NICE::Vector & _alph
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NICE::VVector & _A,
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NICE::VVector & _B) const
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{
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-// std::cerr << "FastMinKernel::hik_prepare_alpha_multiplications" << std::endl;
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-// std::cerr << "alpha: " << alpha << std::endl;
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_A.resize( this->ui_d );
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_B.resize( this->ui_d );
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@@ -189,8 +187,6 @@ void FastMinKernel::hik_prepare_alpha_multiplications(const NICE::Vector & _alph
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for (uint i = 0; i < this->ui_d; i++)
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{
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uint numNonZero = this->X_sorted.getNumberOfNonZeroElementsPerDimension(i);
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- //DEBUG
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- //std::cerr << "number of non-zero elements in dimension " << i << " / " << d << ": " << numNonZero << std::endl;
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_A[i].resize( numNonZero );
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_B[i].resize( numNonZero );
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}
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@@ -259,8 +255,6 @@ double *FastMinKernel::hik_prepare_alpha_multiplications_fast(const NICE::VVecto
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// creating the lookup table as pure C, which might be beneficial
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// for fast evaluation
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double *Tlookup = new double [ hmax * this->ui_d ];
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-// std::cerr << "size of LUT: " << hmax * this->ui_d << std::endl;
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-// sizeOfLUT = hmax * this->d;
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// loop through all dimensions
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@@ -890,7 +884,6 @@ double *FastMinKernel::solveLin(const NICE::Vector & _y,
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for ( uint i = 0; i < sizeOfRandomSubset; i++)
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{
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- cerr << i << " " << sizeOfRandomSubset << " " << perm.size() << " " << _y.size() << " " << _alpha.size() << endl;
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pseudoResidual(perm[i]) = -_y(perm[i]) + (this->d_noise * _alpha(perm[i]));
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for (uint j = 0; j < this->ui_d; j++)
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{
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