how to use word embedding to do document classification etc?
So, one document is a matrix. If I want to use some traditional method like random forest to classify documents, how to use such data?


You can't, at least not directly because traditional methods require a fixed number of features for every instance. In the case of document classification the instance must represent the document, so unless all the documents have exactly the same length (unrealistic) it's impossible to use a set of vectors as features. 

The traditional approach would consist in representing a document with a vector where each cell represents a word in the vocabulary, and the value is for instance the TFIDF weight of the word in the document.