{"action":"created","issue":{"url":"https://api.github.com/repos/rakutentech/stAdv/issues/6","repository_url":"https://api.github.com/repos/rakutentech/stAdv","labels_url":"https://api.github.com/repos/rakutentech/stAdv/issues/6/labels{/name}","comments_url":"https://api.github.com/repos/rakutentech/stAdv/issues/6/comments","events_url":"https://api.github.com/repos/rakutentech/stAdv/issues/6/events","html_url":"https://github.com/rakutentech/stAdv/issues/6","id":381050585,"node_id":"MDU6SXNzdWUzODEwNTA1ODU=","number":6,"title":"My question about L_adv","user":{"login":"hhhzzj","id":37574973,"node_id":"MDQ6VXNlcjM3NTc0OTcz","avatar_url":"https://avatars3.githubusercontent.com/u/37574973?v=4","gravatar_id":"","url":"https://api.github.com/users/hhhzzj","html_url":"https://github.com/hhhzzj","followers_url":"https://api.github.com/users/hhhzzj/followers","following_url":"https://api.github.com/users/hhhzzj/following{/other_user}","gists_url":"https://api.github.com/users/hhhzzj/gists{/gist_id}","starred_url":"https://api.github.com/users/hhhzzj/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hhhzzj/subscriptions","organizations_url":"https://api.github.com/users/hhhzzj/orgs","repos_url":"https://api.github.com/users/hhhzzj/repos","events_url":"https://api.github.com/users/hhhzzj/events{/privacy}","received_events_url":"https://api.github.com/users/hhhzzj/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-11-15T08:29:52Z","updated_at":"2018-11-15T09:17:23Z","closed_at":null,"author_association":"NONE","body":"![251272133292119420](https://user-images.githubusercontent.com/37574973/48539587-95567100-e8f2-11e8-8394-85a420bce7f9.png)\r\nLook at above picture,this is from loss.py.I have a question that our goal is to maximize the distance between logits about target and logits without target,So i think it should be L_adv_2-L_adv_1 instead of L_adv_1-L_adv_2.\r\nAm I missing something?"},"comment":{"url":"https://api.github.com/repos/rakutentech/stAdv/issues/comments/438971764","html_url":"https://github.com/rakutentech/stAdv/issues/6#issuecomment-438971764","issue_url":"https://api.github.com/repos/rakutentech/stAdv/issues/6","id":438971764,"node_id":"MDEyOklzc3VlQ29tbWVudDQzODk3MTc2NA==","user":{"login":"berangerd","id":19334753,"node_id":"MDQ6VXNlcjE5MzM0NzUz","avatar_url":"https://avatars3.githubusercontent.com/u/19334753?v=4","gravatar_id":"","url":"https://api.github.com/users/berangerd","html_url":"https://github.com/berangerd","followers_url":"https://api.github.com/users/berangerd/followers","following_url":"https://api.github.com/users/berangerd/following{/other_user}","gists_url":"https://api.github.com/users/berangerd/gists{/gist_id}","starred_url":"https://api.github.com/users/berangerd/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/berangerd/subscriptions","organizations_url":"https://api.github.com/users/berangerd/orgs","repos_url":"https://api.github.com/users/berangerd/repos","events_url":"https://api.github.com/users/berangerd/events{/privacy}","received_events_url":"https://api.github.com/users/berangerd/received_events","type":"User","site_admin":false},"created_at":"2018-11-15T09:17:23Z","updated_at":"2018-11-15T09:17:23Z","author_association":"MEMBER","body":"We want to minimize `L_adv`, with `L_adv = max(L_adv_1 - L_adv_2, - kappa)`\r\nThe `max` means that `L_adv = L_adv_1 - L_adv_2` if `L_adv_1 - L_adv_2 > - kappa`\r\nand `L_adv = - kappa` if `L_adv_1 - L_adv_2 < - kappa` (in which case we will have a gradient of 0).\r\n\r\nEssentially it gives a stopping condition: if `L_adv_1 - L_adv_2 < 0` by definition the classifier will predict the target label and there is no need to continue increasing the target logit with respect to the other ones. `kappa > 0` is used in arXiv:1608.04644 to \"generate high-confidence adversarial examples\", see in particular Section VIII.D."}}
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