Eigensolutions: Composability as the Antidote to Overfit
11–20 of 23 posts
Re: Eigensolutions: Composability as the Antidote to Overfit
#12The use of "eigen" here seems to have stretched too far beyond its original meaning in mathematics, and in German more generally. In German, "eigen" means "own" like "my own idea." In mathematics, "eigenvalue" is a certain numeric value associated to a matrix or linear operator, which is independent of various representations of that matrix or operator. In that sense, the number is the operator's "own" value, in the…
On the contrary, I've found the article quite refreshing. Using eigen isn't such a big issue if you understand it as the eigen in eigenvector. It's about implementing orthogonal features i.e. Solving non overlapping concerns. Having one way of doing things. Make things easier, less cluttered. The exposé is right on the money and actually even explains it. Perhaps the faux intellectualism is on the other side... <_<
Re: Eigensolutions: Composability as the Antidote to Overfit
#13The use of "eigen" here seems to have stretched too far beyond its original meaning in mathematics, and in German more generally. In German, "eigen" means "own" like "my own idea." In mathematics, "eigenvalue" is a certain numeric value associated to a matrix or linear operator, which is independent of various representations of that matrix or operator. In that sense, the number is the operator's "own" value, in the…
The whole blog _looks_ like a scientific paper with citations, quotes, diagrams and jargon, but none of the arguments made really have any evidence and wind up being circular.
Re: Eigensolutions: Composability as the Antidote to Overfit
#14The use of "eigen" here seems to have stretched too far beyond its original meaning in mathematics, and in German more generally. In German, "eigen" means "own" like "my own idea." In mathematics, "eigenvalue" is a certain numeric value associated to a matrix or linear operator, which is independent of various representations of that matrix or operator. In that sense, the number is the operator's "own" value, in the…
On the contrary, I've found the article quite refreshing. Using eigen isn't such a big issue if you understand it as the eigen in eigenvector. It's about implementing orthogonal features i.e. Solving non overlapping concerns. Having one way of doing things. Make things easier, less cluttered. The exposé is right on the money and actually even explains it. Perhaps the faux intellectualism is on the other side... <_<
When people borrow words from these nomenclatures and change their meaning, it makes their writing pretentious and bloated, not to mention less clear.
Re: Eigensolutions: Composability as the Antidote to Overfit
#15Earlier quoted context omitted.
On the contrary, I've found the article quite refreshing. Using eigen isn't such a big issue if you understand it as the eigen in eigenvector. It's about implementing orthogonal features i.e. Solving non overlapping concerns. Having one way of doing things. Make things easier, less cluttered. The exposé is right on the money and actually even explains it. Perhaps the faux intellectualism is on the other side... <_<
>Perhaps the faux intellectualism is on the other side... It really isn't. Nomenclatures in the sciences and other fields are used for the purpose of clarity and concision; they make communication more effective. For example, when a mathematician mentions an Eigenvalue, other mathematicians know specifically what this object is. That is the point. When people borrow words from these nomenclatures and change their mea…
Even between different scientific disciplines.
For example, what is covariance?
Besides, the criticism was overly pedantic, but alas. The explanation wasn't even that bad.
Decomposition of a design problem in a set of orthogonal questions is exactly what is being described. Solving then the problem by providing solutions that don't overlap is also what is being described.
And the author is right about mentioning that because it's not actually obvious that giving a solution to each "eigenquestions" provide a canonical basis for the solution space, so to speak.
Really it seems that people want to be pedantic just to be pedantic... I don't think such arrogance is warranted here.
Re: Eigensolutions: Composability as the Antidote to Overfit
#16Earlier quoted context omitted.
On the contrary, I've found the article quite refreshing. Using eigen isn't such a big issue if you understand it as the eigen in eigenvector. It's about implementing orthogonal features i.e. Solving non overlapping concerns. Having one way of doing things. Make things easier, less cluttered. The exposé is right on the money and actually even explains it. Perhaps the faux intellectualism is on the other side... <_<
> Shishir Mehrotra (of Coda) wrote about the importance of “Eigenquestions” when framing problems, a term he coined, inspired from his math background: > the eigenquestion is the question where, if answered, it likely answers the subsequent questions as well. > This inspired me to name a symmetrical concept I’ve been pondering for a while: Eigensolutions. The eigensolution is a solution that addresses several key use…
Of course it could have been said in other, simpler terms perhaps, but that can be attributed to stylistic choices. I'm not too offended by that.
It's rare that people rethink something in terms of (multi) linear algebra, it can be a good reframing for an idea.
Re: Eigensolutions: Composability as the Antidote to Overfit
#17>Rather than designing a solution to address only our driving use cases, step back and ask yourself: can we design a solution as a composition of smaller, more general features, that could be used together to address a broader set of use cases? Analogy: when painting a scene, instead of buying every specific color you need, build a palette of a few colors and mix them together as you paint to create the colors you ne…
Re: Eigensolutions: Composability as the Antidote to Overfit
#18Earlier quoted context omitted.
>Perhaps the faux intellectualism is on the other side... It really isn't. Nomenclatures in the sciences and other fields are used for the purpose of clarity and concision; they make communication more effective. For example, when a mathematician mentions an Eigenvalue, other mathematicians know specifically what this object is. That is the point. When people borrow words from these nomenclatures and change their mea…
That's really not how languages work. Even between different scientific disciplines. For example, what is covariance? Besides, the criticism was overly pedantic, but alas. The explanation wasn't even that bad. Decomposition of a design problem in a set of orthogonal questions is exactly what is being described. Solving then the problem by providing solutions that don't overlap is also what is being described. And the…
You are further demonstrating the point that mixing this math language simply creates confusion.
Re: Eigensolutions: Composability as the Antidote to Overfit
#19Earlier quoted context omitted.
That's really not how languages work. Even between different scientific disciplines. For example, what is covariance? Besides, the criticism was overly pedantic, but alas. The explanation wasn't even that bad. Decomposition of a design problem in a set of orthogonal questions is exactly what is being described. Solving then the problem by providing solutions that don't overlap is also what is being described. And the…
Eigenvalues have nothing to do with orthogonality. You are further demonstrating the point that mixing this math language simply creates confusion.
Re: Eigensolutions: Composability as the Antidote to Overfit
#20Earlier quoted context omitted.
That's really not how languages work. Even between different scientific disciplines. For example, what is covariance? Besides, the criticism was overly pedantic, but alas. The explanation wasn't even that bad. Decomposition of a design problem in a set of orthogonal questions is exactly what is being described. Solving then the problem by providing solutions that don't overlap is also what is being described. And the…
Eigenvalues have nothing to do with orthogonality. You are further demonstrating the point that mixing this math language simply creates confusion.