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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
5
votes
Accepted
Is maximum likelihood estimation practical through backpropagation?
Traditionally, machine learning approaches maximize the log-likelihood instead of the actual likelihood.
That is, instead of maximizing $p(Y|X, \theta)$ wrt $\theta$, we instead maximize
$$\log p(Y | …
5
votes
2
answers
177
views
Do tail bounds on probability translate into bounds on expectations?
Here's the specific case that I'm interested in, a nonparametric regression concentration inequality found in these notes: https://www.mit.edu/~rakhlin/courses/mathstat/rakhlin_mathstat_sp22.pdf#page= …
4
votes
Thin Plate Regression Splines mgcv?
The motivation for performing an eigendecomposition of the design matrix is indeed, as you mentioned, to reduce the computational cost of the algorithm. Fitting splines, particularly in the case wher …