{"action":"opened","issue":{"url":"https://api.github.com/repos/bnosac/ruimtehol/issues/6","repository_url":"https://api.github.com/repos/bnosac/ruimtehol","labels_url":"https://api.github.com/repos/bnosac/ruimtehol/issues/6/labels{/name}","comments_url":"https://api.github.com/repos/bnosac/ruimtehol/issues/6/comments","events_url":"https://api.github.com/repos/bnosac/ruimtehol/issues/6/events","html_url":"https://github.com/bnosac/ruimtehol/issues/6","id":386078255,"node_id":"MDU6SXNzdWUzODYwNzgyNTU=","number":6,"title":"difficulty in understanding starspace_embedding() behavior","user":{"login":"fzhang612","id":1038162,"node_id":"MDQ6VXNlcjEwMzgxNjI=","avatar_url":"https://avatars2.githubusercontent.com/u/1038162?v=4","gravatar_id":"","url":"https://api.github.com/users/fzhang612","html_url":"https://github.com/fzhang612","followers_url":"https://api.github.com/users/fzhang612/followers","following_url":"https://api.github.com/users/fzhang612/following{/other_user}","gists_url":"https://api.github.com/users/fzhang612/gists{/gist_id}","starred_url":"https://api.github.com/users/fzhang612/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fzhang612/subscriptions","organizations_url":"https://api.github.com/users/fzhang612/orgs","repos_url":"https://api.github.com/users/fzhang612/repos","events_url":"https://api.github.com/users/fzhang612/events{/privacy}","received_events_url":"https://api.github.com/users/fzhang612/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-11-30T08:03:09Z","updated_at":"2018-11-30T08:03:09Z","closed_at":null,"author_association":"NONE","body":"I am trying to replicate the return value of `starspace_embedding()` function. Here is what I have found so far. \r\n\r\nWhen training a model with ngrams = 1, `starspace(model, 'word1 word2')` = `as.matrix(model)['word1', ] + as.matrix(model)['word2', ]` normalized accordingly. However this doesn't hold when the model trained with ngrams > 1.\r\n\r\nthanks in advance"}}
{"actor":{"display_login":"fzhang612"}}