All Questions
Tagged with machine-learning fa.functional-analysis
10
questions
2
votes
0
answers
29
views
Continuity of Kernel Mean Embeddings
Given some kernel $k: X \times X \to \mathbb{R}$ with RKHS $H_k$ we say that $k$ is characteristic on the space of signed Radon measures over $X$, denoted by $\mathcal{M}(X)$, if the kernel mean ...
- 91
2
votes
0
answers
264
views
Covering/Bracketing number of monotone functions on $\mathbb{R}$ with uniformly bounded derivatives
I am interested in the $\| \cdot \|_{\infty}$-norm bracketing number or covering number of some collection of distribution functions on $\mathbb{R}$.
Let $\mathcal{F}$ consist of all distribution ...
- 93
2
votes
1
answer
156
views
Representer theorem for a loss / functional of the form $L(h) := \sum_{i=1}^n (|h(x_i)-y_i|+t\|h\|)^2$
Let $K:X \times X \to \mathbb R$ be a (positive-definite) kernel and let $H$ be the induced reproducing kernel Hilbert space (RKHS). Fix $(x_1,y_1),\ldots,(x_n,y_n) \in X \times \mathbb R$. For $t \ge ...
- 6,824
1
vote
0
answers
79
views
Relation between minimizer of regularized risk & risk in statistical learning theory
In supervised machine learning, we typically take a Risk Minimization (RM) point of view when formulating a problem. So, what we typically solve for is the following:
$$ R^L(h) = \underset{h\in\...
- 11
4
votes
0
answers
149
views
Can we show equivalence of two distributions based on their statistics?
Let $p,q$ be two distributions on $\mathbb{R}^d$. Let $f:\mathbb{R}^d\times\mathbb{R}^d\rightarrow\mathbb{R}$. Under what conditions does $\mathbb{E}_{x\sim p}f(x,z)=\mathbb{E}_{x\sim q}f(x,z)\ \...
- 57
2
votes
0
answers
193
views
Extension of universal approximation theorem
Let $I_d:=[0,1]^d$ with $d\ge 2$. Define $C(I_d):=\{F: I_d\to\mathbb R \mbox{ is continuous}\}$ and
$$N(I_d):=\{F\in C(I_d): F(x)=\sum_{k=1}^n f_k(v_k\cdot x), \mbox{ where } n\ge 1 \mbox{ and } f_1,\...
user128095
3
votes
0
answers
461
views
Simple (?) question on inner product in reproducing kernel Hilbert space
I'm following the gentle introduction to Reproducing Kernel Hilbert Spaces From Zero to Reproducing Kernel Hilbert Spaces in Twelve Pages or Less by Hal Daumé III. I believe the author fully ...
- 163
8
votes
2
answers
1k
views
VC dimension, fat-shattering dimension, and other complexity measures, of a class BV functions
I wish to show that a function which is "essentially constant" (defined shortly) can't be a good classifier (machine learning). For this i need to estimate the "complexity" of such a class of ...
- 6,824
2
votes
1
answer
1k
views
Packing number of Lipschitz functions
For some $L>0$ say ${\cal L}$ is the space of all $L-$Lipschitz functions mapping $(X,\rho) \rightarrow [0,1]$ where $(X,\rho)$ is a metric space.
For any $\alpha >0$ do we know of a ...
- 2,186
7
votes
1
answer
3k
views
Covering number of Lipschitz functions
What do we know about the covering number of $L$-Lipschitz functions mapping say, $\mathbb{R}^n \rightarrow \mathbb{R}$ for some $L >0$?
Only 2 results I have found so far are,
That the $\infty$-...
- 2,186