{"id":149,"date":"2005-12-11T01:14:43","date_gmt":"2005-12-11T07:14:43","guid":{"rendered":"http:\/\/hunch.net\/?p=149"},"modified":"2005-12-11T01:17:15","modified_gmt":"2005-12-11T07:17:15","slug":"more-nips-papers","status":"publish","type":"post","link":"https:\/\/hunch.net\/?p=149","title":{"rendered":"More NIPS Papers"},"content":{"rendered":"<p>Let me add to John&#8217;s post with a few of my own favourites<br \/>\nfrom this year&#8217;s conference. First, let me say that<br \/>\nSanjoy&#8217;s talk, <em>Coarse Sample Complexity Bounds for Active<br \/>\nLearning<\/em> was also one of my favourites, as was the<br \/>\n<a href=\"http:\/\/books.nips.cc\/papers\/files\/nips18\/NIPS2005_0192.pdf\"><br \/>\nForgettron paper<\/a>.<\/p>\n<p>\nI also really enjoyed the last third of<br \/>\n<a href=\"www.cs.berkeley.edu\/~christos\/\">Christos&#8217;<\/a> talk<br \/>\non the complexity of finding Nash equilibria.\n<\/p>\n<p>\nAnd, speaking of tagging, I think<br \/>\nthe U.Mass Citeseer replacement system<br \/>\n<a href=\"rexa.info\">Rexa<\/a> from the demo track is very cool.\n<\/p>\n<p>\nFinally, let me add my recommendations for specific papers:<\/p>\n<ul>\n<li> Z. Ghahramani, K. Heller: <em>Bayesian Sets<\/em><br \/>\n[no preprint]<br \/>\n(A very elegant probabilistic information retrieval style model<br \/>\nof which objects are &#8220;most like&#8221; a given subset of objects.)\n<\/li>\n<li>T. Griffiths, Z. Ghahramani: <em>Infinite Latent Feature Models and<br \/>\nthe Indian Buffet Process<\/em><br \/>\n[<a href=\"http:\/\/books.nips.cc\/papers\/files\/nips18\/NIPS2005_0130.pdf\"><br \/>\npreprint<\/a>]<br \/>\n(A Dirichlet style prior over infinite binary matrices with<br \/>\nbeautiful exchangeability properties.)\n<\/li>\n<li>K. Weinberger, J. Blitzer, L. Saul: <em>Distance Metric Learning for<br \/>\nLarge Margin Nearest Neighbor Classification<\/em><br \/>\n[<a href=\"http:\/\/books.nips.cc\/papers\/files\/nips18\/NIPS2005_0265.pdf\"><br \/>\npreprint<\/a>]<br \/>\n(A nice idea about how to learn a linear transformation of your<br \/>\nfeature space which brings nearby points of the same class closer<br \/>\ntogether and sends nearby points of differing classes further<br \/>\napart. Convex. Kilian gave a very nice talk on this.)\n<\/li>\n<li> D. Blei, J. Lafferty: <em>Correlated Topic Models<\/em><br \/>\n[<a href=\"http:\/\/www.cs.cmu.edu\/~lafferty\/pub\/ctm.pdf\"><br \/>\npreprint<\/a>]<br \/>\n(Nice trick using the lognormal to induce correlations on the simplex<br \/>\napplied to topic models for text.)\n<\/li>\n<\/ul>\n<p>\nI&#8217;ll also post in the comments a list of other papers that caught my eye but<br \/>\nwhich I haven&#8217;t looked at closely enough to be able to out-and-out<br \/>\nrecommend.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Let me add to John&#8217;s post with a few of my own favourites from this year&#8217;s conference. First, let me say that Sanjoy&#8217;s talk, Coarse Sample Complexity Bounds for Active Learning was also one of my favourites, as was the Forgettron paper. I also really enjoyed the last third of Christos&#8217; talk on the complexity &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/hunch.net\/?p=149\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;More NIPS Papers&#8221;<\/span><\/a><\/p>\n","protected":false},"author":17,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[],"class_list":["post-149","post","type-post","status-publish","format-standard","hentry","category-papers"],"_links":{"self":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/149","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/users\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=149"}],"version-history":[{"count":0,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/149\/revisions"}],"wp:attachment":[{"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=149"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=149"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=149"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}