Applied Regularization Methods for the Social Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)
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Stochastic Calculus via Regularizations (Bocconi & Springer Series, 11)
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Regularization of Inverse Problems (Mathematics and Its Applications, 375)
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Numerical Regularization for Atmospheric Inverse Problems (Environmental Sciences)
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Advanced Classical Electrodynamics: Green Functions, Regularizations, Multipole Decompositions
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The Kepler Problem: Group Theoretical Aspects, Regularization and Quantization, with Application to the Study of Perturbations (Progress in Mathematical Physics, 29)
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Deep Learning with R
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Handbook of Analytic Computational Methods in Applied Mathematics
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Functional Data Analysis with R and MATLAB (Use R!)
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