tag:blogger.com,1999:blog-19803222.post6693956345683802294..comments2024-03-18T01:45:45.724-06:00Comments on natural language processing blog: AI-Stats schedule/papers uphalhttp://www.blogger.com/profile/02162908373916390369noreply@blogger.comBlogger6125tag:blogger.com,1999:blog-19803222.post-22051345828072548562009-05-12T10:56:00.000-06:002009-05-12T10:56:00.000-06:00酒店經紀PRETTY GIRL 台北酒店經紀人 ,禮服店 酒店兼差PRETTY GIRL酒店公關 酒...酒店經紀PRETTY GIRL <A HREF="http://www.taipeilady.com/" REL="nofollow" TITLE="台北酒店經紀人">台北酒店經紀人</A> ,<A HREF="http://tw.myblog.yahoo.com/jw!qZ9n..6QEhhc0LkItOBm/" REL="nofollow" TITLE="禮服店">禮服店</A> 酒店兼差PRETTY GIRL<A HREF="http://www.mashow.org/" REL="nofollow" TITLE="酒店公關">酒店公關</A> 酒店小姐 彩色爆米花<A HREF="http://blog.xuite.net/jkl338801/blog/" REL="nofollow" TITLE="酒店兼職">酒店兼職</A>,酒店工作 彩色爆米花<A HREF="http://tw.myblog.yahoo.com/jw!BIBoU5SeBRs21nb_ajFpncbTqXds" REL="nofollow" TITLE="酒店經紀">酒店經紀</A>, <A HREF="http://mypaper.pchome.com.tw/news/thomsan/3/1310065116/20080905040949/" REL="nofollow" TITLE="酒店上班">酒店上班</A>,酒店工作 PRETTY GIRL<A HREF="http://tw.myblog.yahoo.com/jw!rybqykeeER6TH3AKz1HQ5grm/" REL="nofollow" TITLE="酒店喝酒">酒店喝酒</A>酒店上班 彩色爆米花<A HREF="http://mypaper.pchome.com.tw/news/jkl338801/" REL="nofollow" TITLE="台北酒店">台北酒店</A>酒店小姐 PRETTY GIRL<A HREF="http://www.mashow.org/" REL="nofollow" TITLE="酒店上班">酒店上班</A>酒店打工PRETTY GIRL<A HREF="http://www.tpangel.com/" REL="nofollow" TITLE="酒店打工">酒店打工</A>酒店經紀 彩色爆米花Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-19803222.post-91310290172008465272007-02-10T18:22:00.000-07:002007-02-10T18:22:00.000-07:00My sense (though I've never been) is that it's con...My sense (though I've never been) is that it's content is similar to NIPS/UAI, but is perhaps tier 2, rather than tier 1 (though I also sense it is on the upswing). Ask me again in April, though.<BR/><BR/>And yes, "fast" is very popular... although by pure frequency, "learning" would have to be a stop word (occurs more frequently than any word except "for")... fast comes in with seven counts, and efficient with 6. Kernel and classification both have 5, losing to Bayesian which has 6. Ironically, on my sorting, the word that appears last (you can figure out why if you think of how I sort) is "accurate" :).halhttps://www.blogger.com/profile/02162908373916390369noreply@blogger.comtag:blogger.com,1999:blog-19803222.post-60936096168626993362007-02-10T18:18:00.000-07:002007-02-10T18:18:00.000-07:00This comment has been removed by the author.halhttps://www.blogger.com/profile/02162908373916390369noreply@blogger.comtag:blogger.com,1999:blog-19803222.post-28599484845905691192007-02-10T18:03:00.000-07:002007-02-10T18:03:00.000-07:00I've heard that AISTATS is roughly on par with ICM...I've heard that AISTATS is roughly on par with ICML and UAI.<BR/><BR/>It seems like the hot word for this conference this year is "fast", just based on a simple word count of the titles. :)Kevin Duhhttps://www.blogger.com/profile/07407894290644783502noreply@blogger.comtag:blogger.com,1999:blog-19803222.post-52228452130508758332007-02-10T18:01:00.000-07:002007-02-10T18:01:00.000-07:00This comment has been removed by the author.Kevin Duhhttps://www.blogger.com/profile/07407894290644783502noreply@blogger.comtag:blogger.com,1999:blog-19803222.post-89724165702374884962007-02-10T12:38:00.000-07:002007-02-10T12:38:00.000-07:00For some one who doesn't understand the relationsh...For some one who doesn't understand the relationship of the various ML/AI conferences, where does AISTAT place in the content/quality spectrum ? (I only know places like COLT, ICML, and NIPS)Suresh Venkatasubramanianhttps://www.blogger.com/profile/15898357513326041822noreply@blogger.com