PDF-Scalable KMeans Bahman Bahmani Stanford University Stanford CA bahmanstanford

edu Benjamin Moseley 8727 University of Illinois Urbana IL bmosele2illinoisedu Andrea Vattani 8727 University of California San Diego CA avattanicsucsdedu Ravi Kumar Yahoo Research Sunnyvale CA ravikumaryahoo inccom Sergei Vassilvitskii Yahoo Researc. stanfordedu dph kleinbercscornelledu jurecsstanfordedu ABSTRACT An increasingly common feature of online communities and social media sites is a mechanism for rewarding user achievements based on a system of badges Badges are given to users for part cornelledu Thorsten Joachims Department of Computer Science Cornell University Ithaca NY USA tjcscornelledu ABSTRACT The means clustering algorithm is one of the most widely used e64256ective and best understood clustering methods How ever successful Although it o64256ers no accuracy guarantees its simplicity and speed are very appealing in practice By augmenting kmeans with a very simple ran domized seeding technique we obtain an algorithm that is 920log competitive with the optimal clustering PieterAbbeelpabbeel@cs.stanford.eduMorganQuigleymquigley@cs.stanford.eduAndrewY.Ngang@cs.stanford.eduComputerScienceDepartment,StanfordUniversity,Stanford,CA94305,USAAbstractInthemodel-basedpolicysear *Correspondence:dbergmann@stanford.eduDepartmentofBiology,StanfordUniversity,Stanford,CA94305-5020,USAHowardHughesMedicalInstitute,Stanford,USAFulllistofauthorinformationisavailableattheendofthearticl Stanford University. Scalable K-Means++. K-means Clustering. 2. Fundamental problem in data analysis and machine learning. “By far . the most popular clustering algorithm . used in scientific and industrial applications” [. David . Kaser. Lecture Series. Lorcan Dempsey / . @. LorcanD. Indiana University, . 7 October 2012. How terrific to see you are the featured lecturer this year.   Just thought I'd mention that David . Commutativity. Rule: Designing Scalable Software for Multicore Processors. Austin T. Clements, M. . Frans. . Kaashoek. , . Nickolai. . Zeldovich. , Robert T. Morris, and Eddie Kohler. MIT CSAIL and Harvard University. Processors. Presented by . Remzi. Can . Aksoy. *Some slides . are. . borrowed from a ‘Papers We Love’ . Presentation. EECS 582 – F16. 1. Outline. The . Scalable Commutativity Rule: . Whenever interface operations commute, they can be implemented in a way that scales. 1. MW  . 12:50-2:05pm . in Beckman . B100. Profs: Serafim . Batzoglou. & Gill . Bejerano. CAs. : . Jim . Notwell. & Sandeep . Chinchali. CS273A. Lecture 6: Gene Regulation II. . http://cs273a.stanford.edu/. 1. CS273A. Lecture . 5: . Non Coding . Genes. . http://cs273a.stanford.edu/. Lecture slides, problem sets, etc.. Course communications via Piazza. Auditors please sign up too. Third Tutorial next week. . 1. MW  . 1:30-2:50pm . in . Clark . S361*. (behind . Peet’s. ). Profs: Serafim . Batzoglou. & Gill . Bejerano. CAs. : . Karthik. . Jagadeesh. . & . Johannes . Birgmeier. * Mostly: track on website/piazza. Professor Zare has received numerous honors and awards. They include: Phi Lambda Upsilon's Fresenius Award (1974), Michael Polanyi Medal, the Gas Kinetics Group of the Royal Society of Chemistry (1979 Large scale computing systems. Scalability . issues. Low level and high level communication abstractions in scalable systems. Network interface . Common techniques for high performance communication.