{"action":"created","issue":{"url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/279","labels_url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/279/labels{/name}","comments_url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/279/comments","events_url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/279/events","html_url":"https://github.com/papers-we-love/papers-we-love/pull/279","id":56335994,"number":279,"title":"Papers on Dimensionality Reduction","user":{"login":"tchitra","id":5332137,"avatar_url":"https://avatars.githubusercontent.com/u/5332137?v=3","gravatar_id":"","url":"https://api.github.com/users/tchitra","html_url":"https://github.com/tchitra","followers_url":"https://api.github.com/users/tchitra/followers","following_url":"https://api.github.com/users/tchitra/following{/other_user}","gists_url":"https://api.github.com/users/tchitra/gists{/gist_id}","starred_url":"https://api.github.com/users/tchitra/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tchitra/subscriptions","organizations_url":"https://api.github.com/users/tchitra/orgs","repos_url":"https://api.github.com/users/tchitra/repos","events_url":"https://api.github.com/users/tchitra/events{/privacy}","received_events_url":"https://api.github.com/users/tchitra/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":14,"created_at":"2015-02-03T05:36:45Z","updated_at":"2015-05-28T22:37:04Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/papers-we-love/papers-we-love/pulls/279","html_url":"https://github.com/papers-we-love/papers-we-love/pull/279","diff_url":"https://github.com/papers-we-love/papers-we-love/pull/279.diff","patch_url":"https://github.com/papers-we-love/papers-we-love/pull/279.patch"},"body":"I've added a few papers on the theory of dimensionality reduction. A lot of this work is used to theoretically justify the performance of a variety of machine learning techniques and heuristics such as random forests, approximate least-squares and compressed sensing. The papers included are:\r\n\r\n1. \"The Fast Johnson-Lindenstrauss Transform\" (N. Ailon, B. Chazelle) — Only paper not from arXiv, was in a SIAM Journal and taken directly from B. Chazelle's personal website [0]\r\n2. \"A Sparse Johnson-Lindenstrauss Transform\" (A. Dasgupta, R. Kumar, T. Sarlós) — arXiv/cs/1004:4240; STOC 2010 proceedings\r\n3. \"Towards a unified theory of sparse dimensionality reduction in Euclidean space\" (J. Bourgain, S. Dirksen, J. Nelson) — arXiv/cs/1311.2542; Accepted in an AMS Journal but unpublished at the moment\r\n\r\nI'd be willing to give a talk on one of these papers (presumably not the last one, though, as it is quite deep and hard to cover in a short talk!)\r\n\r\n[0] https://www.cs.princeton.edu/~chazelle/pubs/FJLT-sicomp09.pdf\r\n"},"comment":{"url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/comments/106619271","html_url":"https://github.com/papers-we-love/papers-we-love/pull/279#issuecomment-106619271","issue_url":"https://api.github.com/repos/papers-we-love/papers-we-love/issues/279","id":106619271,"user":{"login":"zeeshanlakhani","id":202820,"avatar_url":"https://avatars.githubusercontent.com/u/202820?v=3","gravatar_id":"","url":"https://api.github.com/users/zeeshanlakhani","html_url":"https://github.com/zeeshanlakhani","followers_url":"https://api.github.com/users/zeeshanlakhani/followers","following_url":"https://api.github.com/users/zeeshanlakhani/following{/other_user}","gists_url":"https://api.github.com/users/zeeshanlakhani/gists{/gist_id}","starred_url":"https://api.github.com/users/zeeshanlakhani/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zeeshanlakhani/subscriptions","organizations_url":"https://api.github.com/users/zeeshanlakhani/orgs","repos_url":"https://api.github.com/users/zeeshanlakhani/repos","events_url":"https://api.github.com/users/zeeshanlakhani/events{/privacy}","received_events_url":"https://api.github.com/users/zeeshanlakhani/received_events","type":"User","site_admin":false},"created_at":"2015-05-28T22:37:04Z","updated_at":"2015-05-28T22:37:04Z","body":"@tchitra thanks. On the licenses though, the Fast Johnson-Lindenstrauss Transform paper, for example, has an explicit copyright on the bottom: `Copyright © by SIAM. Unauthorized reproduction of this article is prohibited`. So, we'd have to go w/ a link for something like that."}}