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https://github.com/Steffo99/appunti-magistrali.git
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43 lines
2 KiB
TeX
43 lines
2 KiB
TeX
\newcommand{\par}[1] {\left({#1}\right)}
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\newcommand{\arr}[1] {\left[{#1}\right]}
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\newcommand{\hsh}[1] {\left\{{#1}\right\}}
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\newcommand{\abs}[1] {\left|{#1}\right|}
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\newcommand{\basisCanon} {\mathbf{\hat{e}}}
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\newcommand{\basisCanonElement}[1][i] {\basisCanon_{#1}}
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\newcommand{\varietyAffine}[2][X] {\mathscr{#1}\par{#2}}
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\newcommand{\smol} {\epsilon}
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\newcommand{\derivativeDirectionalSimple}[3][f] {{#1}'\par{#2_0; #3}}
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\newcommand{\derivativeDirectional}[3][f] {\frac{d #1 \par{#2_0; #3}}{d \smol}}
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\newcommand{\derivativePartial}[3][f] {\frac{\partial #1 \par{#2_0}}{\partial x_{#3}}}
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\newcommand{\derivativePartialOutput}[4][f] {\frac{\partial #1_{#3} \par{#2_0}}{\partial x_{#4}}}
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\newcommand{\derivativeGradientSimple}[2][f] {\nabla_{#1} \par{#2_0}}
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\newcommand{\continueField}[1][1] {\mathcal{C}^{#1}}
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\newcommand{\hessianSimple}[2][f] {\mathbf{\nabla}^2_{#1} \par{#2_0}}
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\newcommand{\hessianElement}[4][f] {\frac{\partial^2 #1 \par{#2}}{\partial #2_{#3}\ \cdot\ \partial #2_{#4}}}
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\newcommand{\iacobianSimple}[2][f] {\mathbf{J}_{#1} \par{#2}}
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\newcommand{\fmlDataset} {\mathbf{D}}
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\newcommand{\fmlDatasetSize} {P}
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\newcommand{\fmlDatasetTrain} {\fmlDataset_{train}}
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\newcommand{\fmlDatasetValidate} {\fmlDataset_{validate}}
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\newcommand{\fmlDatasetTest} {\fmlDataset_{test}}
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\newcommand{\fmlInputs} {\mathbf{X}}
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\newcommand{\fmlIndex} {i}
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\newcommand{\fmlInput}[1][\fmlIndex] {\mathbf{x}_{#1}}
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\newcommand{\fmlInputSize} {n}
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\newcommand{\fmlInputField}[1][\fmlInputSize] {\mathbb{X}^{#1}}
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\newcommand{\fmlElementIndex} {j}
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\newcommand{\fmlInputElement}[1][\fmlIndex\fmlElementIndex] {x_{#1}}
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\newcommand{\fmlInputElementField} {\mathbb{X}}
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\newcommand{\fmlOutputs} {\mathbf{y}}
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\newcommand{\fmlOutput}[1][\fmlIndex] {y_{#1}}
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\newcommand{\fmlOutputField} {\mathbb{Y}}
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\newcommand{\fmlClassifier} {f}
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\newcommand{\fmlModel} {\fmlClassifier^*}
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\newcommand{\fmlHypothesisSpace} {\mathcal{H}}
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\newcommand{\fmlComplexity} {c}
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\newcommand{\fmlComplexityCoefficient} {\lambda}
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\newcommand{\fmlLoss} {V}
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