Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.
10
votes
Accepted
Sampling from a categorical distribution
Let me unravel your question to remove all the not-so-relevant fluff around it.
Given a tuple of $n$ values of the form $(p_i)_{1\leq i\leq n}$, where each $p_i\in(0,1)$, the question is to charac …
1
vote
Learn this distribution from samples? What is the sample complexity?
$\ell_2$ won't be "interesting." You can learn any discrete distribution to $\ell_2$ distance $\phi$ with probability $1-\gamma$ with $O( \log(1/\gamma)/\phi^2 )$ samples, with no dependence on the d …