# Tag Info

### What kind of answer does TCS want to the question "Why do neural networks work so well?"

There are a bunch of "no free lunch" theorems in machine learning, roughly stating that there can be no one master learning algorithm that performs uniformly better than all other algorithms (see, e.g....

### What kind of answer does TCS want to the question "Why do neural networks work so well?"

There are two main gaps in our understanding of neural networks: optimization hardness and generalization performance. Training a neural network requires solving a highly non-convex optimization ...
Accepted

### Is BPP vs. P a real problem after we know BPP lies in P/poly?

Not sure how much of an answer this is, I'm just indulging in some rumination. Question 1 could be equally asked about P $\neq$ NP and with a similar answer -- the techniques/ideas used to prove the ...
Accepted

### Circuit and Formula Lower Bounds for Separating Sparse Sets of Strings

Yes, any such pair can be separated by a formula of size $O(n)$. More generally, any disjoint pair $P,N\subseteq\{0,1\}^n$ of size $s=|P|+|N|$ can be separated by a decision tree of size $O(s)$, which ...

### What kind of answer does TCS want to the question "Why do neural networks work so well?"

Another take on this question, to add to @Aryeh's remarks: For many other models of learning, we know the "shape" of the hypothesis space. SVMs are the best example of this, in that what you're ...
Accepted

### Does Approx Carathéodory's theorem implies dimensionality reduction

The approximate Caratheodory theorem goes back to the 60s, and probably way earlier than that (it follows for example from the mistake bound of the preceptron algorithm analysis). As for the ...