These are opinions that please the machine spirit.
^The topology section of the thesis I linked to.
It was an informal discussion in our research group.
But the need for topology came in because it was a debate on the flexibility of real number tensors versus what programs can do in practice. So I boiled both of them down to sets and am looking at their behavoir.
The modularity issue in deep learning is just the connected property. But it is pretty easy to introduce a noncontinuous function. In fact, this is common.
https://knowledge.uchicago.edu/record/2215
The issue is that connectedness is a valuable property to use, most of the time. So deeper networks are better. More data is better.
Program synthesis is also aided by the connected property, but relies on it less. So, not useful for modularity per se, but it can probably bridge larger data dead spots, or rough patches in data.
^a
Sure. They are different. Human minds can understand the vitali set. Machine learning's best tools are only able to approximate borel measurable sets, despite taking the name of "universal approximators".
Humans are cool.
I should be reading about automated reasoning logics. But cognitive stuff is good too.
https://www.frontiersin.org/articles/10.3389/fnins.2014.00265/full
@sapphire @BowsacNoodle @johnbudd1350 @Agartha_Noble @hikari
Downside: potentially no internet
My boss gave me 133 or so pages of math to read before Friday morning. I need to find something in this kind of logic to improve upon before then. Sleep should be happening now.
What’s Decidable About Program Verification Modulo Axioms?
https://arxiv.org/pdf/1910.10889.pdf
Decidable Synthesis of Programs with Uninterpreted Functions
https://arxiv.org/pdf/1910.09744.pdf
Decidable Verification of Uninterpreted Programs
https://arxiv.org/pdf/1811.00192.pdf
This looks like it is the same book.
https://www.cs.utexas.edu/~swarat/pubs/PGL-049-Plain.pdf
Possible free access through univerities
https://ieeexplore.ieee.org/document/9646874
> You will comply, even as the technology moves on from the point that such rituals make sense.
Classic Java culture of programmers.
Yeah. Rust is basically just Java, for people too young to remember how over-marketed Java was.
It is more advanced. Yes. Very, more so than regular programs in a lot of ways.
It is a concept that comes out of the formal methods community. A more descriptive title is more like "automated program synthesis via mathematical logic and deep learning".
I am pretty curious about how to use automated reasoning systems to help discover new things, use and verify old ideas, and generally make my life easier.
Current events I try to keep up on
- Math Logic community (The Journal of Symbolic Logic)
- Statistics community (JASML, AoS)
- Algebra community (JoA, JoAG, JoPaAA, SIGSAM)
- Formal Methods community (CAV/TACAS)
Passing the learning curve up to current events
- Abstract Algebra (Dummit, Foote)
- Commutative Algebra (Eisenbud)
- Algebraic Geometry (Hartshorne)
- Mathematical Logic (Mendelson)
- Model Theory (Marker)