Learning of manifolds Also topological data analysis; other hip names to follow 2014-08-19 – 2020-06-23
Dimensionality reduction Wherein I teach myself, amongst other things, feature selection, how a sparse PCA works, and decide where to file multidimensional scaling 2015-03-22 – 2020-06-23
Restricted isometry properties Plus incoherence, irrepresentability, and other uncertainty bounds for a sparse world, and maybe frame theory, what’s that now? 2017-06-12 – 2020-03-09
Random change of time Stochastic processes derived by varying the rate of time’s passage, which is more convenient than I imagined 2015-08-05 – 2020-02-10
Inner product spaces The most highly developed theory of squaring things 2019-01-01 – 2019-02-11
Learning on manifolds Finding the lowest bit of a krazy straw, from the inside 2011-10-21 – 2018-11-16
Learning on manifolds Finding the lowest bit of a krazy straw, from the inside 2011-10-21 – 2018-11-16
Linear algebra If the thing is twice as big, the transformed version of the thing is also twice as big. {End} 2011-04-06 – 2018-08-07
AutoML hyperparameter selection with the use of yet more hyperparameters 2017-07-17 – 2017-08-30
Statistical learning theory Eventually including structural risk minimisation, risk bounds, hopefully-uniform convergence rates, VC-dimension, generalisation-and-stability framings etc 2016-07-06 – 2016-08-16