query: L1 L2 regularization
positive_passages.docid: 153341
positive_passages.text: Lasso regression feature selection
negative_passages.docid: 38739
negative_passages.text: Restrictions on universal generalization
negative_passages.docid: 130047
negative_passages.text: Is it possible to use regularization methods on the Harmonic Series?
negative_passages.docid: 42302
negative_passages.text: Use of Holder inequality in gradient estimate for harmonic function.
negative_passages.docid: 157923
negative_passages.text: RMSProp Squared Gradients
negative_passages.docid: 44139
negative_passages.text: Back transformation of an MLR model
negative_passages.docid: 36758
negative_passages.text: Triangle inequality for L2 norm
negative_passages.docid: 156700
negative_passages.text: Why do we only see $L_1$ and $L_2$ regularization but not other norms?
negative_passages.docid: 133323
negative_passages.text: Intuitive explanation of Lovasz Softmax loss for Image Segmentation problems
negative_passages.docid: 12981
negative_passages.text: Coordinate descent soft-thresholding update operator for LASSO
negative_passages.docid: 80085
negative_passages.text: Why does the accuracy not change, when applying different alpha values in L2 regularisation
negative_passages.docid: 107595
negative_passages.text: Iteratively minimizing the function
negative_passages.docid: 103939
negative_passages.text: Why doesn't regularization solve Deep Neural Nets hunger for data?
negative_passages.docid: 84044
negative_passages.text: Generic contour smoothing with shading
negative_passages.docid: 98605
negative_passages.text: Ridge/Lasso regression negative Lambda
negative_passages.docid: 148798
negative_passages.text: Closed form and gradient calculation for linear regression
negative_passages.docid: 115419
negative_passages.text: Combined numerical minimization and maximization