Sparse model selection
September 5, 2016 — October 2, 2020
estimator distribution
functional analysis
high d
linear algebra
model selection
probability
signal processing
sparser than thou
statistics
On choosing the right model and regularisation parameter in sparse regression, which turn out to be nearly the same, and closely coupled to doing the regression. There are some wrinkles.
🏗 Talk about when degrees-of-freedom penalties work, when cross-validation and so on.
1 FOCI
The new hotness sweeping the world is FOCI, a sparse model selection procedure (Azadkia and Chatterjee 2019) based on Chatterjee’s ξ statistic as an independence test. (Chatterjee 2020). Looks interesting.
2 Stability selection
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For now see mplot for an introduction.
3 Relaxed Lasso
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4 Dantzig Selector
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5 Garotte
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6 Degrees-of-freedom penalties
See degrees of freedom.
7 References
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