Only if the "true" data actually lives in a lower dimensional manifold and the data acurrately can encode it with low noise. I doubt anyone can tell who you will vote for depending on which cat videos you liked, no matter how magic your regressor.
I do think that the most significant components of a personality will likely be targetable with a relatively low nuclear norm.
And, for example, where someone's proclivity on the exploration/exploitation spectrum, if you will, (IE, how strongly do they respond to fear-based messaging) falls is probably quite predictable from a spectrum of likes.
Cat pictures may be less informative, but not all of these people clicked exclusively on feline fuzzy photos.
I'm not an expert on personality so won't disagree (except to say that I am a little sceptical of a static personality profile actually existing and I think people who always vote a certain way would be the easiest to regress and also the most useless to target).
As I said in another post, it really depends on what part of your privacy you are trying to protect. It is also a mistake to think of anything on the internet as a private forum.
I think it is falsifiable. More precisely, the claim is that the most significant features for psychoanalytic purposes will be contained in the model after training even with low nuclear norm.
It’s possible for the most salient features for this purpose to not be in the model.
It was unclear the way I first said it.
