The Living Thing / Notebooks

The Living Thing / Notebooks :

Optimisation of model functions for experiment design — [ Surrogate optimisation methods for optimisinf functions ] —
2017-04-11… 2019-07-18
Sparse regression —
2016-06-23… 2019-02-25
Bayesian sparsity —
2019-01-08… 2019-01-08
Multiple testing —
2015-04-22… 2018-11-05
Measure concentration inequalities — [ On being 80% sure you are only 20% wrong ] —
2014-11-25… 2017-12-07
AutoML — [ hyperparameter selection with the use of yet more hyperparameters ] —
2017-07-17… 2017-08-30
Post-selection inference — [ Adaptive data analysis without cheating ] —
2017-08-20… 2017-08-20
Model/hyperparameter selection —
2016-04-15… 2017-08-20
Bayesian model selection —
2017-08-20… 2017-08-20
Statistical learning theory for dependent data —
2016-11-03… 2017-07-10
Model averaging — [ On keeping many incorrect hypotheses and using them all as one goodish one ] —
2017-06-20… 2017-07-04
Generalisation in neural networks — [ Generalisation for street fighters ] —
2017-02-12… 2017-06-20
Compressed sensing / compressed sampling — [ The fanciest ways of counting zero ] —
2014-08-18… 2017-06-14
Model complexity penalties — [ Information criteria, degrees of freedom etc ] —
2015-04-22… 2017-05-03
Independence, conditional, statistical —
2016-04-21… 2017-02-15
Effective sample size —
2016-11-21… 2017-02-07
M-estimation —
2016-07-11… 2016-10-10
Stability (in learning) —
2016-05-25… 2016-10-05
Cross Validation —
2016-09-05… 2016-09-27
Penalised/regularised regression —
2016-06-23… 2016-09-15
Sparse model selection —
2016-09-05… 2016-09-08
Statistical learning theory — [ Eventually including structural risk minimisation, risk bounds, hopefully-uniform convergence rates, VC-dimension, generalisation and stability framings ] —
2016-07-06… 2016-08-16

The Living Thing is a collection of the perpetually-in-progress learning notebooks of Dan MacKinlay. If you want to talk about stuff here, use the comment form or the private contact from.
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