On Tue, Nov 6, 2018 at 3:55 PM Stefan van der Walt <stef...@berkeley.edu> wrote:
> On Tue, 06 Nov 2018 12:11:13 -0800, Robert Kern wrote: > > Popular, but quite misleading, in the same way that not every 2-dim array > > is a matrix. As someone who works on tensor machine learning methods once > > complained to me. > > Are you referring to vectors, structured arrays, or something else? > I was responding to this statement by Chuck: > I think the current popular terminology is `tensors` for `multidimensional arrays`. Mostly popularized by Tensorflow. But the "tensors" that flow through Tensorflow are mostly just multidimensional arrays and have no tensor-algebraic meaning. Similarly, a 2-dim array (say, a grayscale intensity image) doesn't necessarily have a matrix-algebraic interpretation, either. A 640x480 grayscale image is not a linear transformation from RR^640 to RR^480. It's just a collection of numbers that are convenient to organize as a 2D grid. This seems to be a pain point with some tensor methods ML researchers who have to explain their work to an audience that seems to think that Tensorflow must make their lives (and theses) easy. :-) -- Robert Kern
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