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#ICYMI on the BGSE Data Science blog: Randomized Numerical Linear Algebra (RandNLA) For Least Squares: A Brief Introduction

January 20, 2017

Dimensionality reduction is a topic that has governed our (the 2017 BGSE Data Science cohort) last three months. At the heart of topics such as penalized likelihood estimation (Lasso, Ridge, Elastic Net, etc.), principal component analysis and best subset selection lies the fundamental trade-off between complexity, generalizability and computational feasibility.

David Rossell taught us that even if we have found a methodology to compare across models, there is still the problem of enumerating all models to be compared… read the full post by Robert Lange ’17 on Barcelona GSE Data Scientists

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